Softwr

Business Intelligence · head to head

Domo vs Elasticsearch

Domo logo

Domo

Business Intelligence

Business cloud for modern enterprises

From
$30000/year
Rated
-
Full reviewWebsite
Elasticsearch logo

Elasticsearch

Database & Data Management

The heart of the Elastic Stack for search and analytics

From
Free
Rated
-
Full reviewWebsite

The short version

  • Only Elasticsearch 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; Elasticsearch eventual consistency model with 1-second default refresh interval, not suitable for real-time transactional requirements
  • They diverge on capability: Domo covers 1000+ Connectors, Elasticsearch covers Full-text Search.

Where they differ

Only the attributes on which Domo and Elasticsearch actually diverge.

Attributes where Domo and Elasticsearch differ
AttributeDomoElasticsearch
Starting price$30000/yearFree
Free tierNoYes
PlatformsWeb, Mobile, ApiLinux, Windows, macOS, Docker, Kubernetes
CategoryBusiness IntelligenceDatabase & Data Management

Identical on both: pricing model (Unknown), user rating (Not yet rated), founded (2010).

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 Elasticsearch

  • Full-text Search
  • Real-time Analytics
  • Distributed Architecture
  • RESTful API
  • Schema-free JSON
  • Aggregations
  • Machine Learning
  • Kibana

Both cover

  • Web support

What people use each for

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

Domo

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

Elasticsearch

  • Real-time applicationsnot Domo
  • Content managementnot Domo
  • User profilesnot Domo
  • Mobile backendsnot Domo
  • Cachingnot 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

Elasticsearch

  • Eventual consistency model with 1-second default refresh interval, not suitable for real-time transactional requirements
  • No support for ACID transactions or rollbacks; updates delete and re-insert documents
  • JVM-dependent architecture requires careful memory management and monitoring to prevent garbage collection issues at scale

Pricing, plan by plan

Domo

$30000/year

No published plan breakdown. See the Domo review.

Elasticsearch

Free
  • Self-ManagedFree
    • Open source
    • Self-hosted
  • Elasticsearch Cloud$16.4/month
    • Managed service
    • 14-day free trial

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 Elasticsearch if

  • You need full-text search.
  • You want to start without paying.
  • You work on Linux, Windows, macOS, Docker, Kubernetes.
  • You also want real-time analytics.
Elasticsearch review

Questions people ask

Is Domo or Elasticsearch better?
Neither clearly leads. Domo starts at $30000/year and Elasticsearch at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Domo or Elasticsearch?
Elasticsearch has a free tier; the other does not. Paid plans start at $30000/year for Domo and Free for Elasticsearch.
Does Domo or Elasticsearch run on more platforms?
Domo runs on Web, Mobile, Api. Elasticsearch runs on Linux, Windows, macOS, Docker, Kubernetes.
Can I use Elasticsearch for free?
Yes. Elasticsearch 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 Elasticsearch is typically brought in for.
What can Domo do that Elasticsearch cannot?
Domo covers 1000+ Connectors, Real-time Data, Mobile BI, Collaboration. Elasticsearch covers Full-text Search, Real-time Analytics, Distributed Architecture, RESTful API. 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
Elasticsearch: Is Elasticsearch free?

Yes, Elasticsearch can be deployed as free and open-source software for self-managed installations. Elastic Cloud managed service starts at $16.40 per month, with a free 14-day trial available.

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
Elasticsearch: Can I use Elasticsearch without Kibana?

Yes, Elasticsearch is a search engine independent of Kibana. Kibana is a visualization and analytics tool that works with Elasticsearch but is optional. You can use the Elasticsearch API directly for searching.

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
Elasticsearch: Does Elasticsearch support real-time indexing?

Elasticsearch indexes data with a refresh interval, typically 1 second. Data becomes searchable after the refresh cycle, making it near-real-time but not instantaneous. This can be configured but impacts performance.

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
Elasticsearch: What are Elasticsearch's scaling limitations?

Elasticsearch requires careful operational management at scale, including shard balancing, heap sizing, and monitoring. Large clusters can suffer from garbage collection issues and become expensive to operate.

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
Elasticsearch: Does Elasticsearch support transactions and rollbacks?

No, Elasticsearch does not support ACID transactions or rollbacks. Updates are expensive operations that delete and re-insert documents, making it unsuitable for transactional workloads.

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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