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Other options for your stack · 7 options

Elasticsearch alternatives

Choose a database that fits your query patterns and operating capacity—not just Elasticsearch’s feature list.

Edited by Edward Teller· Updated

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Elasticsearch is a search database that teams can self-host, but operating and scaling it takes cluster experience. The alternatives below span relational databases, analytical SQL engines, document stores and managed Postgres. They are not drop-in replacements: choose based on whether your app needs search, analytics or a general data layer. Listed prices start at $0 or are marked n/a for some options; check each provider’s pricing for usage costs before planning a production migration.

01Why people leave Elasticsearch

Reduce operational work

A Reddit thread describes the complexity of running Elasticsearch and argues that PostgreSQL can be easier to manage for some full-text workloads.

Avoid license uncertainty

Some developers say Elasticsearch’s license change pushed them to OpenSearch and made them reluctant to return.

Fit the data model

If your workload is relational, document-centric or analytical, a database built around that model may be a simpler fit than a search cluster.

02The alternatives, ranked by fit

  1. Best open-source default

    PostgreSQL

    PostgreSQL is a free, open-source database server for teams that want a relational data layer and can operate their own database. Its listed starting price is n/a, with a free plan; hosting and operational work remain yours. Treat it as a replacement when your application needs a relational database, not as a guaranteed drop-in for Elasticsearch’s search workflows.

    Trade-off: You supply hosting and operations; the listing does not specify search feature parity.

    PostgreSQL reviewElasticsearch vs PostgreSQL
    8.4/10
    from
    Free    free plan
  2. Best for analytics

    ClickHouse

    ClickHouse is a fit when the workload is real-time analytics on large datasets and the team wants fast analytical SQL. It is open source and self-hostable, with its listed starting price marked n/a. That makes it an alternative for analytical queries, rather than a like-for-like search API; plan for database operations if you self-host.

    Trade-off: Columnar analytics is a different workload from general search.

    ClickHouse reviewElasticsearch vs ClickHouse
    8.3/10
    from
    Custom
  3. Best embedded analytics

    DuckDB

    DuckDB suits local SQL analytics, embedded analytical queries and work directly on Parquet or CSV. It is open source, self-hostable and has a free plan, with the listed starting price marked n/a. Developers can consider it when search infrastructure is being used for local data analysis, not when they need a distributed search service.

    Trade-off: Its stated fit is local and embedded analytics, not cluster search.

    DuckDB review
    8.5/10
    from
    Free    free plan
  4. Best for document apps

    MongoDB

    MongoDB is a stronger fit when application data is document-shaped and the team wants one query API for document-centric operations and search. It is self-hostable, and the listed price starts at $8 with a free plan. Compare the actual search needs and deployment costs before moving workloads; flexible schemas still need deliberate design.

    Trade-off: Flexible schemas need deliberate design; listed pricing does not establish production cost.

    MongoDB reviewElasticsearch vs MongoDB
    7.2/10
    from
    $8/mo    free plan
  5. Best for shared fast data

    Redis

    Redis fits applications needing shared, fast data, including AI agents that need retrieved context. It is open source and self-hostable; its listed price starts at $5 with a free plan. Consider it when the required data access matches that role, rather than assuming it replaces Elasticsearch’s search behavior or indexing model.

    Trade-off: Production fit depends on deployment choices and cost.

    Redis reviewElasticsearch vs Redis
    7.5/10
    from
    $5/mo    free plan
  6. Best for MySQL apps

    MySQL

    MySQL is the practical alternative when an application already uses MySQL or needs a GPL database. It is open source and self-hostable, but the listed price starts at $178.33 despite a free plan. That price is not enough to estimate a production bill: the edition and server size affect cost, so check the intended deployment before migrating.

    Trade-off: Production costs and licensing depend on edition and server size.

    MySQL review
    7.3/10
    from
    $178.33/mo    free plan
  7. Best managed Postgres

    Neon

    Neon pairs managed Postgres with branching and backend services. It can suit teams moving a project to managed Postgres or creating isolated preview databases, with a listed starting price of $15 and a free plan. It is a hosted option, not a self-hostable replacement; compare usage-based costs against your workload before committing.

    Trade-off: Managed Postgres means a hosted deployment and usage-dependent bills.

    Neon review
    7.6/10
    from
    $15/mo    free plan

03Side by side

ToolScoreFromFree planBest for
Elasticsearch (current)7.5$99/moNoAI apps needing hybrid retrieval
PostgreSQL8.4FreeYesTeams that want open-source database software
ClickHouse8.3CustomNoReal-time analytics on large datasets
DuckDB8.5FreeYesLocal SQL analytics and data wrangling
MongoDB7.2$8/moYesApps built around document-shaped data
Redis7.5$5/moYesApps needing shared, fast data
MySQL7.3$178.33/moYesApplications already built on MySQL
Neon7.6$15/moYesApps needing managed Postgres

Prices from each vendor's pricing page, checked Nov 6, 2026.

Questions people ask

Is Elasticsearch still popular?

Popularity is not a reliable reason to keep or replace a search database. Elasticsearch remains a candidate for teams that need hybrid retrieval or search across large datasets and can manage cluster operations. Compare alternatives against your query requirements, migration effort and operating capacity.

Does Netflix use Elastic?

We can’t confirm Netflix’s current use of Elastic from a verified public reference. Customer usage also does not establish whether Elasticsearch fits your application. Evaluate the database against your own search workload, API requirements, operating capacity and expected cost.

Is Elasticsearch the same as Kibana?

No. Elasticsearch and Kibana are separate products; developers often encounter them together in log-management setups. Replacing Elasticsearch does not, by itself, establish what should replace Kibana or any other part of that stack. Map each component to its role before planning a migration.