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Business Intelligence · head to head

Domo vs TimescaleDB

Domo logo

Domo

Business Intelligence

Business cloud for modern enterprises

From
$30000/year
Rated
-
Full reviewWebsite
TimescaleDB logo

TimescaleDB

Databases

Time-series database built on PostgreSQL for real-time analytics

From
Free
Rated
-
Full reviewWebsite

The short version

  • Only TimescaleDB has a free tier, so it costs nothing to try first.
  • Each has a real cost: Domo pricing is not published; contracts start around $30,000 per year minimum, making budget planning difficult without a sales conversation; TimescaleDB inherits PostgreSQL write path limitations, creating a ceiling on ingestion throughput
  • They diverge on capability: Domo covers 1000+ Connectors, TimescaleDB covers Time-series Optimization.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Domo and TimescaleDB actually diverge.

Attributes where Domo and TimescaleDB differ
AttributeDomoTimescaleDB
Starting price$30000/yearFree
Free tierNoYes
PlatformsWeb, Mobile, ApiLinux, macOS, Windows, Docker, Kubernetes, Cloud (AWS, GCP, Azure)
CategoryBusiness IntelligenceDatabases
Founded20102012

Identical on both: pricing model (Unknown), user rating (Not yet rated).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in Domo

  • 1000+ Connectors
  • Real-time Data
  • Mobile BI
  • Collaboration
  • App Development
  • Salesforce
  • Google Analytics
  • Facebook

Only in TimescaleDB

  • Time-series Optimization
  • PostgreSQL Extension
  • Automatic Partitioning
  • Continuous Aggregates
  • Native Compression
  • Full SQL Support
  • Real-time Analytics
  • PostgreSQL

Both cover

  • Web support

What people use each for

The jobs each tool is most often brought in to do.

Domo

  • Self-service analyticsnot TimescaleDB
  • Data explorationnot TimescaleDB
  • Ad-hoc reportingnot TimescaleDB
  • Collaborative analysisnot TimescaleDB
  • Embedded analyticsnot TimescaleDB

TimescaleDB

  • Monitoringnot Domo
  • IoT datanot Domo
  • Financial datanot Domo
  • Log analyticsnot Domo
  • Observabilitynot Domo

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Domo

  • Pricing is not published; contracts start around $30,000 per year minimum, making budget planning difficult without a sales conversation
  • Visualization customization is limited compared to specialized tools like Tableau, with rigid chart types and restricted pixel-level dashboard layouts
  • Version control and merge options for dataflows are very limited, making multi-developer projects prone to conflicts and overwrites
  • Workflows cannot be edited once deployed; any changes require rebuilding from scratch
  • Semantic layer lacks code-based governance, with metric definitions scattered inside individual cards rather than in a centralized governed location

TimescaleDB

  • Inherits PostgreSQL write path limitations, creating a ceiling on ingestion throughput
  • Operational complexity increases significantly at scale, requiring expertise in chunk tuning and autovacuum management
  • Bloom filter indexes on compressed columns can return incorrect query results before upgrade
  • PostgreSQL 15 support ending June 2026, forcing mandatory upgrades to PostgreSQL 16 or later

Pricing, plan by plan

Domo

$30000/year

No published plan breakdown. See the Domo review.

TimescaleDB

Free
  • Open SourceFree
    • Self-hosted TimescaleDB
    • MIT-licensed core
    • Full PostgreSQL compatibility
  • Scale Plan (Cloud)$36/month
    • Compute and storage charges
    • Multi-node HA
    • Unlimited VPCs

Which should you pick?

Choose Domo if

  • You need 1000+ connectors.
  • You work on Web, Mobile, Api.
  • You also want real-time data.
Domo review

Choose TimescaleDB if

  • You need time-series optimization.
  • You want to start without paying.
  • You work on Linux, macOS, Windows, Docker, Kubernetes, Cloud (AWS, GCP, Azure).
  • You also want postgresql extension.
TimescaleDB review

Questions people ask

Is Domo or TimescaleDB better?
Neither clearly leads. Domo starts at $30000/year and TimescaleDB at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Domo or TimescaleDB?
TimescaleDB has a free tier; the other does not. Paid plans start at $30000/year for Domo and Free for TimescaleDB.
Does Domo or TimescaleDB run on more platforms?
Domo runs on Web, Mobile, Api. TimescaleDB runs on Linux, macOS, Windows, Docker, Kubernetes, Cloud (AWS, GCP, Azure).
Can I use TimescaleDB for free?
Yes. TimescaleDB has a free tier, so you can try it without paying. Domo starts at $30000/year.
What is Domo best used for?
Domo is most often used for self-service analytics, data exploration, ad-hoc reporting, collaborative analysis. Of those, self-service analytics and data exploration are not what TimescaleDB is typically brought in for.
What can Domo do that TimescaleDB cannot?
Domo covers 1000+ Connectors, Real-time Data, Mobile BI, Collaboration. TimescaleDB covers Time-series Optimization, PostgreSQL Extension, Automatic Partitioning, Continuous Aggregates. Both handle Web support.

Answered from the vendors’ own pages

Domo: Does Domo offer a free tier or trial?

Domo does not publish pricing on its website and does not offer a standard free tier. The platform uses a consumption-based credit model with minimum viable deployments starting around $30,000 per year. A free trial may be available upon request from the sales team.

Source
TimescaleDB: Is TimescaleDB free?

Yes. TimescaleDB is free and open source under the Timescale License. The managed cloud service offers a free trial with $1,000 in credits expiring in 30 days.

Source
Domo: What data sources can Domo connect to?

Domo connects to over 1,000 pre-built connectors covering cloud applications, databases, advertising platforms, file services, spreadsheets, enterprise systems, and data warehouses. Custom integrations are possible via API.

Source
TimescaleDB: What database does TimescaleDB run on top of?

TimescaleDB is a PostgreSQL extension that runs on top of PostgreSQL. You retain full PostgreSQL compatibility including SQL queries, transactions, and ecosystem tools.

Source
Domo: Can I self-host Domo or is it cloud-only?

Domo is a fully cloud-native, SaaS platform with no self-hosted option available. All data and applications run on Domo's cloud infrastructure.

Source
TimescaleDB: How much can TimescaleDB compress data?

TimescaleDB offers transparent columnar compression that can reduce storage by up to 95%. Newer data remains in row-oriented format for fast writes, while older data is automatically compressed to the column store.

Source
Domo: What does the credit-based pricing model mean?

Domo charges credits based on data consumption and platform activity. One credit roughly equals processing one million rows of data, though actual burn rate varies with workflows. Users purchase credit packages providing team access with unlimited user seats; only activity consumes credits, not dashboards or team size.

Source
TimescaleDB: Does TimescaleDB require manual partitioning?

No. TimescaleDB handles automatic time-based partitioning through hypertables. Data is automatically chunked based on time intervals, requiring no manual partition management.

Source
Domo: Does Domo include AI features and what do they cost?

Domo AI features are free as part of your contract, including DomoGPT for AI chat queries. Premium AI capabilities are available through Domo AI Pro, which uses consumption-based pricing on a per-use basis.

Source
TimescaleDB: What PostgreSQL versions does TimescaleDB support?

As of October 2025, TimescaleDB requires PostgreSQL 16 or greater. PostgreSQL 15 support will end with the June 2026 release, after which all instances must upgrade to PostgreSQL 16.

Source
Domo: Can multiple teams collaborate on the same dashboard in Domo?

Yes, Domo supports team collaboration on shared dashboards and datasets. However, version control and merge capabilities for dataflows are limited, which can cause conflicts when multiple developers work on the same project.

Source
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