TimescaleDB vs InfluxDB: which to choose

TimescaleDB or InfluxDB: when each one fits the time-series workload

TimescaleDB fits teams already on PostgreSQL who need SQL joins against relational data, while InfluxDB 3 Core fits teams standardized on line protocol and InfluxQL or SQL over Parquet files. The choice usually turns on where your metrics, sensor or event data has to meet the rest of your estate. If the time-series rows must join with customers, assets or accounts in PostgreSQL, the extension keeps that work in one engine. If your collectors, dashboards and skills already center on InfluxDB's write APIs and query languages, InfluxDB 3 Core keeps that pattern intact. Three decision drivers should be settled before you compare benchmarks. First, check your existing PostgreSQL skills and operating model, since TimescaleDB adds an extension to a database you must already patch, back up and fail over. Second, read the Timescale License terms if you plan to offer the database as a service: the license permits internal on-premises or cloud use but restricts offering it as a service, and that restriction applies only to the Community Edition code under the Timescale License. Third, decide whether high availability or historical query must come from the open-source build. InfluxDB reserves those capabilities for its Enterprise tier, so budget for that edition or design around the gap. Before you commit, confirm with each vendor which features your target edition includes, and test your real ingest rate, query shapes and retention policy in your own environment. Ask for written answers on license terms for your intended use, and on how each product handles upgrades. Those checks will settle the decision more reliably than general feature lists.

Which platform fits which scenario

This table maps common TimescaleDB and InfluxDB scenarios to the platform that usually fits better and the condition that decides it. Read each row against your own data model, team skills and availability requirements. The main takeaway is that the choice often turns on whether telemetry must live beside relational data in PostgreSQL.

Scenario	Better fit	Deciding condition
Existing PostgreSQL estate	TimescaleDB	Your team already runs, backs up and upgrades PostgreSQL, and you can add an extension under the license terms that apply to your build.
Joins between telemetry and customer or asset tables	TimescaleDB	You need standard SQL joins against relational tables in the same database. InfluxDB 3 Core supports SQL, but its data model is built around measurements and Parquet files rather than a general relational store.
Telegraf or line protocol ingestion	InfluxDB 3 Core	Your collectors already write line protocol or use Telegraf, and the 1.x and 2.x write APIs are part of your current tooling. TimescaleDB can ingest data, but you would build or configure the pipeline yourself.
Object-storage-first retention	InfluxDB 3 Core	You want history persisted as Apache Parquet on S3, Azure or GCP storage. Confirm how your retention, compaction and query latency targets behave on your chosen storage before committing.
Offering the database as a hosted service	Depends on the TimescaleDB build	The Apache 2 Edition can be sold as a service, while the Timescale License Community Edition cannot be offered as a service. Confirm your licensing position with Tiger Data and with counsel before you design the offering.
Built-in high availability	InfluxDB 3 Enterprise, or TimescaleDB with external tooling	InfluxDB lists high availability and read replicas in Enterprise, not Core. PostgreSQL offers replication but needs external tools for automatic failover, so confirm which HA stack you will operate.
Historical query and single series indexing	InfluxDB 3 Enterprise	The InfluxDB documentation places historical query capability and single series indexing in Enterprise. Core users should confirm what their query patterns need before selecting it.
Continuous aggregates and columnstore compression	TimescaleDB Community Edition	These features are available only in the Community Edition, so you must accept the Timescale License terms to use them. Confirm whether your internal use or service model fits those terms.

How each platform is built and what that means for operations

TimescaleDB and InfluxDB 3 Core make different bets about where time-series data lives and who operates it. One runs inside PostgreSQL and inherits its operational practice. The other is a standalone Rust service with its own storage, query and plugin model. The cards below trace each design choice to the tasks your team will own.

TimescaleDB runs as a PostgreSQL extension

TimescaleDB loads into a standard PostgreSQL server, so hypertables sit alongside ordinary tables in the same database. Backups, roles, connection pooling and replication follow PostgreSQL practice, and your DBAs can apply existing runbooks. Check that the extension version is compatible with the PostgreSQL major version you run, because the extension and the server must be upgraded together. Confirm the build you need under the Timescale License before you rely on it.

PostgreSQL failover needs external tooling

PostgreSQL supports hot standbys, synchronous and asynchronous replication, but it does not detect a failed primary and promote a standby on its own. TimescaleDB inherits that gap, so high availability for a self-hosted deployment means choosing and operating an external failover manager. Ask your team who owns that tool, how it is tested, and how client connections are redirected after promotion.

Major upgrades follow PostgreSQL procedures

Major PostgreSQL upgrades use pg_dumpall with restore, pg_upgrade, or logical replication, and logical replication allows a major upgrade with only several seconds of downtime. For TimescaleDB, you must also plan the extension version against each target PostgreSQL major. Minor releases do not change the storage format, so they are mostly executable replacement and restart. Budget test time for the extension path, not only the server path.

InfluxDB 3 Core is a standalone Rust service

InfluxDB 3 Core is built in Rust on Apache Arrow and DataFusion and runs as its own process with its own HTTP API. It is not a database you add to an existing server, so it needs its own install, monitoring, backup and upgrade process. Operations staff who already run PostgreSQL will learn a new service, not extend a known one. Confirm that your team can operate a second database platform alongside the ones already in production.

Parquet storage on object storage or disk

InfluxDB 3 Core persists data as Apache Parquet on S3, Azure, GCP or local disk. That makes the data files readable by other Arrow and Parquet tools, but it also moves durability and cost decisions to the storage layer. Decide early whether the data sits on local disk or object storage, who owns bucket lifecycle and access policy, and how restores are tested. Verify the exact backup and compaction behavior for your chosen storage with InfluxData before sizing the deployment.

Embedded Python VM for plugins

InfluxDB 3 Core includes an embedded Python VM that runs plugins and triggers inside the server. This can remove an external job runner for simple processing, but it also puts custom code in the database process. Your security team should review who may deploy plugins, how they are versioned, and what they can reach on the host or network. Treat plugin code as part of your change control scope, not as configuration.

Capability comparison from supplied facts

This table sets TimescaleDB, running inside PostgreSQL, against InfluxDB 3 Core on the dimensions that most often decide a time-series shortlist: license, query and write interfaces, relational joins, storage, availability and authentication. Where a capability sits behind a paid or commercial edition, the cell says so, and where the supplied facts do not settle an answer, the cell names what to confirm before you commit.

Capability	TimescaleDB (PostgreSQL extension)	InfluxDB 3 Core
License	PostgreSQL License for PostgreSQL. Extension code outside the tsl directory is Apache 2.0; tsl code is under the Timescale License	MIT or Apache 2.0 at the user's choice for InfluxDB 3 Core; commercial code is kept separate and closed
Query language	Full PostgreSQL SQL, including the time_bucket functions and hypertable queries	SQL, InfluxQL and Flight SQL
Write protocol	Standard PostgreSQL clients and SQL inserts; no line protocol is documented in the supplied facts	Line protocol over an HTTP API on port 8181, compatible with the 1.x and 2.x write APIs
Relational joins	Joins with ordinary PostgreSQL tables in the same database and query	SQL queries over its own tables; confirm join scope and table model against current documentation
Storage format	PostgreSQL storage, with hypertable chunks; columnstore (Hypercore) is Community Edition only	Apache Parquet on object storage (S3, Azure, GCP) or local disk, built on Arrow and DataFusion
High availability	PostgreSQL synchronous and asynchronous replication; automatic failover needs external tools	Single-node Core; high availability is listed as an InfluxDB 3 Enterprise feature
Read replicas	Hot standby servers serve read-only queries using PostgreSQL replication	Read replicas are listed as an InfluxDB 3 Enterprise feature
Historical query and series indexing	Available on the PostgreSQL database with standard query behavior; confirm retention and chunk settings for your data	Historical query capability and single series indexing are listed as InfluxDB 3 Enterprise features
Authentication methods	PostgreSQL documents password, GSSAPI, SSPI, LDAP, RADIUS, certificate, PAM and OAuth; MD5 is deprecated in favor of SCRAM	Confirm supported authentication options and token handling in the InfluxDB 3 Core documentation
Commercial add-ons	Continuous aggregates, retention policies and job scheduling are Community Edition only, not the Apache 2 Edition	High availability, read replicas and historical query sit in Enterprise; confirm current edition terms with InfluxData

What the Timescale License and InfluxDB editions allow

The Apache 2 Edition is the part of TimescaleDB whose source code sits outside the tsl directory, so it is licensed under the Apache License 2.0. It leaves out the features that Tiger Data places only in Community Edition, so the operating model is narrower. Because of the Apache license, you can run it internally and sell it as a service.

Included: the core extension code licensed under Apache 2.0, from outside the tsl directory.
Excluded: continuous aggregates, the columnstore (Hypercore), data retention policies, job scheduling and time_bucket_gapfill.
Internal use: permitted under the Apache 2.0 terms.
Offering as a service: permitted, which is the main reason to choose this build for a hosted product.
Cost: the license carries no fee. Your costs are staff time, hosting and any support contract you buy separately.

Before you choose this build, confirm that your workload does not depend on compression, retention or scheduled rollups, because operating without them changes how you manage storage and jobs.

TimescaleDB Community Edition adds the features that Tiger Data reserves for it: continuous aggregates, the columnstore, data retention policies, job scheduling and time_bucket_gapfill. These features are covered by the Timescale License, which applies to code inside the tsl directory and to built shared object files with -tsl in their names. The license lets you run the software in your own on-premises or cloud infrastructure for free, but it does not allow you to offer it as a service.

Included: the extension features listed above, built from code under the Timescale License.
Free use: installing and running it in your own on-premises or cloud infrastructure at no charge under the license terms.
Not permitted: offering Community Edition as a service to third parties.
Paid routes: the license itself carries no fee. Managed hosting is available only through Tiger Cloud, and any support contract is a separate purchase.
Package contents: the repository separates Apache-licensed and Timescale-licensed files, so confirm which shared objects your package installs.

Have counsel read the Timescale License against your planned use, especially if a customer or affiliate will consume the database through your product. The Tiger Data editions page is the place to confirm the feature split for the version you run.

Why high availability and historical query change the shortlist

The high availability gap is the first thing to price before you commit. PostgreSQL gives you hot standbys that serve read-only queries, plus synchronous replication, where a commit waits for standbys, and asynchronous replication. What it does not give you is failover itself: PostgreSQL does not detect a primary failure and notify the standby, so automatic failover depends on external tools such as Patroni or a comparable cluster manager that your team selects, installs and operates. With TimescaleDB, that same cluster layer sits underneath the extension, so you still own the HA design, the failover tests and the on-call runbook. InfluxDB 3 Core, by contrast, documents high availability, read replicas and historical query with single series indexing as features of InfluxDB 3 Enterprise, so a clustered topology is a licensing decision, not only an operations one.

These needs change cost in different places. On the PostgreSQL side, most of the cost is recurring engineering time for failover automation, replication monitoring, backup and point-in-time recovery testing, and standby capacity, all of it staffed by your team or a partner such as DeployOpen under a written scope. On the InfluxDB side, the cost moves to a commercial Enterprise agreement, whose price you must request in writing. Ask InfluxData which features your topology actually needs and whether they are in Enterprise, and ask for the Enterprise terms in the same quote. Also confirm the Enterprise support and upgrade terms, since they will shape your recurring spend more than the license fee does at first glance.

What drives the running cost of each

Running cost for either platform depends less on the license line than on where the database runs, who operates it and how often you must upgrade it. The cards below cover the cost drivers that differ between TimescaleDB on PostgreSQL and InfluxDB 3, and what to put in a written scope so a quote can follow. DeployOpen does not publish prices, and a quote follows from the written scope.

Infrastructure and storage footprint

TimescaleDB stores hypertable chunks in PostgreSQL tables on your servers or cloud volumes, while InfluxDB 3 Core writes Apache Parquet files to object storage or local disk. The storage layout, compression settings and retention windows set the disk and object storage bill. Ask for sizing based on your ingest rate, series cardinality and retention period, and confirm whether compression is included in the edition you plan to run. Size storage from retention, not from the default, because retention drives most of the recurring footprint.

PostgreSQL skills already on staff

If your team already runs PostgreSQL, TimescaleDB adds an extension to a stack you operate, so the main cost is extending existing skills rather than hiring. InfluxDB 3 Core brings its own query languages, HTTP write API and Python plugin runtime, which means new runbooks and training. Ask in the quote which tasks DeployOpen would carry in the first year and which would move to your team, and whether the work covers both PostgreSQL and the extension.

Tiger Cloud plan tiers and support add-ons

Tiger Cloud is priced by published plan tiers, with Performance and Scale listed at monthly rates and Enterprise at custom pricing. Production support by phone or ticket with a response target is a separate paid add-on on the lower tiers, and the Enterprise plan includes it. If you compare a managed TimescaleDB plan with self-hosting, add plan fees, support add-ons and any data egress or storage charges to the self-hosted infrastructure and labor figures before you decide.

InfluxDB Enterprise licensing for high availability

InfluxDB 3 Core is the open-source build, while the features for historical query, single series indexing, high availability and read replicas sit in InfluxDB 3 Enterprise. If you need HA on InfluxDB, the Enterprise license becomes a recurring cost line that the open-source build does not carry. On the TimescaleDB side, PostgreSQL streaming replicas are included in the open-source server, but automatic failover needs an external tool that you install and operate. Ask InfluxData for Enterprise terms in writing and compare them with the failover tooling and its maintenance effort.

Upgrade cadence and support windows

PostgreSQL ships a new major version about once a year and supports each major for five years, so the upgrade effort recurs on a predictable schedule. PostgreSQL 14 is supported until November 12, 2026, which makes it a near-term upgrade for any TimescaleDB estate still on it. Ask for the upgrade of both PostgreSQL and the TimescaleDB extension to be scoped and priced as a recurring item, including testing and the rollback plan. InfluxDB upgrades follow the InfluxData release cycle, so ask how long each major line receives support.

Monitoring and operational tooling

Both platforms need metrics, alerting on ingest lag, disk growth and replication health, and backups with tested restores. TimescaleDB inherits PostgreSQL tooling such as continuous archiving and point-in-time recovery, plus connection pooling with PgBouncer, which you run and monitor yourself. InfluxDB requires its own monitoring and backup approach for object storage data. Ask the quote to name which dashboards, alert rules and restore tests are included and who owns them after handover.

Moving data from one platform to the other

This sequence moves a time-series workload from InfluxDB to TimescaleDB, or the reverse, without losing history or breaking the writers that feed it. Each step ends with a check you can run, so the cutover happens only after both platforms agree on the data.

Inventory measurements, tags and retention
The platform team lists every measurement, tag set, field type, write rate and retention rule in the current InfluxDB instance, and notes which series are kept longest. Map each one to a planned hypertable, its time column, its segmentation keys and the retention policy it needs. The step closes when the team has a signed-off table of source series against target tables, with any gaps flagged for the data owners to decide.
Map line protocol and InfluxQL to SQL
Engineers translate every write path and every query that matters into the target model. Line protocol writers get a schema mapping for tags and fields, and each InfluxQL or Flux query used by dashboards, alerts or reports is rewritten as SQL, with joins to relational reference data added where the new model allows it. The step closes when each query has a reviewed SQL equivalent and a documented result comparison plan.
Rebuild dashboards, tasks and alerts
Dashboard owners recreate panels against the new data source, and engineers rebuild InfluxDB tasks, plugins and triggers as scheduled jobs, continuous aggregates or external alerting rules. Retention rules are recreated on the target and checked against the inventory. Nothing transfers automatically at this point, so each rebuilt item is tracked by name. The step closes when every dashboard and alert on the list has an owner and a tested replacement.
Backfill historical data
The team exports history from InfluxDB, typically as line protocol or through a query export, and loads it into the target in time-ordered batches. Raw points and their timestamps carry over, while dashboard definitions, tasks and alert logic do not. Row counts, time ranges and sampled aggregates are compared per measurement against the source. The step closes when the reconciliation report shows no unexplained differences for each series in scope.
Run both platforms in parallel
Writers send data to both systems through a dual-write or fan-out layer, and the team compares live query results from the old and new dashboards over a period agreed in advance. Differences in aggregation windows, null handling and timestamp precision are logged and resolved before cutover. The step closes when the agreed comparison period ends with the open differences documented and accepted by the data owners.
Cut over writers and retire the source
Writers are switched to the target one group at a time, starting with the least critical, and the source is kept read-only for a fallback window. Operators confirm ingestion lag, error rates and dashboard freshness after each group moves. The source instance is decommissioned only after the rollback path has been tested and the final backup has been verified. The step closes with a written cutover record listing each writer, its switch time and its verification result.

What implementing each involves and where projects run long

A PostgreSQL-based TimescaleDB deployment starts with an ordinary PostgreSQL build plus the extension, so the first work item is confirming that your PostgreSQL major version is one the extension supports and that your upgrade path will keep both in step. The design work then moves to hypertable layout: choosing the time column, chunk interval and any space partitioning, and creating hypertables with the tsdb.hypertable table option shown in the project quick start. Retention and compression policies need the same care, because they decide what is deleted and when. Note that continuous aggregates, the columnstore, retention policies and job scheduling belong to the Community Edition under the Timescale License, so confirm your build before designing around them. High availability and backup come last and are often underestimated: PostgreSQL's built-in replication does not detect failure or promote a standby, so you must select and test failover tooling and point-in-time recovery yourself.

An InfluxDB 3 Core deployment front-loads different decisions. You configure the object storage backend (S3, Azure or GCP) or local disk where Parquet files land, size the write path for line protocol over the HTTP API on port 8181, and plan plugin design for the embedded Python VM, including how plugins are tested and deployed. Client migration is usually the largest task: applications that write through the 1.x or 2.x APIs may keep working, but read paths built on InfluxQL, Flux or your own dashboards need review. Where projects run long, the reasons are consistent across both platforms. Query translation takes longer than expected because SQL joins against relational data, InfluxQL and Flux do not behave identically. Schema and tag design is hard to reverse once series cardinality grows. Authentication integration with your identity provider is often scoped late. Upgrade testing is skipped, then needed under pressure. Ask each vendor and your implementation partner for a written test plan covering these four areas before committing to a timeline.

Questions buyers ask before choosing or hiring help

Can TimescaleDB run on our existing PostgreSQL servers?

Yes, TimescaleDB is installed as an extension into a PostgreSQL database, so it runs on PostgreSQL you already operate, provided your team can add the extension to that cluster. The TimescaleDB README describes it as a PostgreSQL extension for real-time analytics on time-series and event data. Confirm three things before you commit: which PostgreSQL major version your build supports, whether your managed PostgreSQL provider allows third-party extensions, and which TimescaleDB build you need, because continuous aggregates, the columnstore, retention policies and job scheduling are only in the Community Edition. The one-line install script in the README is for local development and testing only, so production installs need a planned, documented process.

What does the Timescale License prevent for a hosted service?

The Timescale License lets you install TimescaleDB Community Edition on your own on-premises or cloud infrastructure and run it free of charge, but it does not allow you to offer the Community Edition as a service. The Apache 2 Edition, which sits under Apache License 2.0, can be sold as a service. If your product gives customers access to a hosted time-series database, you need to read the license against your exact offering and confirm the position with your counsel. Internal analytics for your own staff is a different case from a service sold to outside users, so describe the use case precisely when you ask for a license review.

Does InfluxDB 3 Core support high availability?

InfluxDB 3 Core does not provide high availability, read replicas or historical query features on its own. The InfluxDB 3 Core documentation says those capabilities belong to InfluxDB 3 Enterprise, which adds historical query capability, single series indexing, high availability and read replicas. If your design needs failover for ingest or queries, plan for that cost in the licensing decision, or design redundancy around Core in a way you can verify. Confirm current feature boundaries and the Enterprise licensing terms directly with InfluxData before you assume them.

What does a migration from InfluxDB need from our team?

A migration needs an inventory of what you write and query, a mapping of your data model, and a plan for the query language change. Writes in InfluxDB 3 Core use line protocol over an HTTP API on port 8181, and the 1.x and 2.x write APIs are supported, which can ease ingest cutover. Queries move from InfluxQL or Flux to SQL on the TimescaleDB side, and dashboards, alerts and any Python plugins need to be rebuilt or rewritten. Your team should own the schema decisions, the retention rules and the acceptance tests for data parity. Teams that already run PostgreSQL usually need less retraining for SQL, but they still need a rehearsal on a copy of the data.

What drives the cost of running either option?

Cost is driven by who operates the database, how much data you keep and at what resolution, and which paid features you need. For TimescaleDB, the software is free under the Timescale License for self-hosting, so your costs are infrastructure, the people who run PostgreSQL, backups, monitoring and upgrades, plus any Tiger Cloud subscription if you choose the managed service. For InfluxDB, the open-source Core is free to use under MIT or Apache 2.0, but high availability and historical query features sit in the Enterprise tier, so licensing becomes a major line item. Ask any vendor or partner for a written quote that separates one-time work (design, migration, hardening) from recurring work (support, upgrades, storage growth, on-call).

Can our team run TimescaleDB or InfluxDB without outside help?

A team that already runs PostgreSQL in production can usually run TimescaleDB, but it still needs to own high availability, backups, point-in-time recovery and upgrades of both PostgreSQL and the extension. PostgreSQL does not include automatic failover software, so you need external tooling and tested runbooks. A team with no PostgreSQL experience, or one that is new to time-series operations, will need more time to learn retention, compression and capacity planning. Assess your skills honestly against the operational list, and confirm whether your staff can cover on-call, security patching and upgrade windows without outside help.

How long does a time-series database migration usually take?

The duration depends on data volume, the number of writers and readers, how many dashboards and alerts must be rebuilt, and how much compliance evidence you must produce. Schedules are set in a written scope, and DeployOpen's engagements are usually fixed-scope, so timelines are agreed before work starts. Ask any partner for a plan that lists each phase, the acceptance criteria for data parity and cutover, and the dependencies on your teams. Because this page does not carry a supplied duration for either migration, confirm the estimate against a pilot on a representative slice of your data.

How DeployOpen helps choose, implement or migrate

DeployOpen plans, implements, hardens, backs up and documents self-hosted open-source platforms inside your own cloud accounts, data centers or air-gapped networks. The cards below cover the decisions and checks that come before a TimescaleDB or InfluxDB rollout, and the work that follows it. DeployOpen is not a vendor partner or reseller, favors neither platform, and does not issue audit reports or certifications.

Workload and query fit review

Before choosing, write down your ingest rate, retention windows, cardinality of series and the queries your dashboards and jobs run. Note whether those queries join against customer, asset or ticket tables already in PostgreSQL. A scoped review can test both candidates against a representative sample of your own data, so the decision rests on your workload rather than on published benchmarks. Ask for the test plan and acceptance criteria in the written scope.

License and edition mapping

TimescaleDB splits its code between Apache 2.0 and the Timescale License, and features such as continuous aggregates and the columnstore sit in the Community Edition. InfluxDB 3 Core is MIT or Apache 2.0 at your choice, while its high availability and historical query features are reserved for Enterprise. DeployOpen can map which features your team needs to which edition, and document what internal use and service delivery mean for your organization. Confirm the interpretation with your legal counsel.

Ingestion and migration planning

If you already write to InfluxDB 1.x or 2.x, or to a PostgreSQL schema, the migration path differs. InfluxDB 3 Core accepts line protocol and is compatible with the 1.x and 2.x write APIs, while TimescaleDB takes SQL inserts and hypertable conversion. DeployOpen can plan the cutover, dual-write period and rollback steps as a fixed-scope deliverable, with the data validation checks written down before any production traffic moves.

High availability and failover design

PostgreSQL offers hot standby replicas and synchronous or asynchronous replication, but it does not detect a primary failure or promote a standby on its own, so automatic failover depends on external tools. For InfluxDB, the high availability and read replica features belong to the Enterprise tier. DeployOpen can design, test and document the failover runbook for your chosen platform, including which component owns failover decisions and how they are tested.

Hardening, backup and recovery

Backup and point-in-time recovery look different on each side. For TimescaleDB, plan on PostgreSQL continuous archiving, and check how the extension behaves during restores. For InfluxDB 3 Core, data persists as Parquet on object storage or local disk, so backup scope depends on where you put it. DeployOpen can harden the database and access layers, configure backups and restore tests, and document the results so your team can repeat them.

Upgrade and support planning

Both platforms need an upgrade plan. PostgreSQL releases a new major version about once a year and supports each for five years, and PostgreSQL 14 is supported until November 12, 2026. TimescaleDB upgrades must track PostgreSQL major versions as well as the extension. A retainer can cover scheduled upgrades, testing and ongoing support. Fixed-scope work covers the initial build and documentation. Ask for the upgrade calendar and the support hours in writing before you sign.

Compliance evidence preparation

If your data falls under a regulated workload, your assessor will want evidence of access control, backup testing, change records and audit logging for the database. DeployOpen can prepare the systems, configurations and documentation that support those controls, and organize the evidence for your independent auditor. DeployOpen does not issue audit reports, attestations or certifications, and it does not decide which platform meets a given requirement.

TimescaleDB vs InfluxDB