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Known limitations or unsupported functionalities

Quesma is designed for analytical text queries such as in observability or security. It does literal case-insensitive matches. It does not do tokenization, natural language processing or scoring.

  • Unsupported example: You need top 10 results for query car and expect to find article with word automobile.
  • Good fit: Searching for logs such as InvalidPassword should also match InvalidPasswordError without * as required in Elastic.

Software and hardware requirements

We recommend setting up at least 2 CPU cores and 2GBs of RAM for the Quesma container. The requirements may vary depending on the workload and the number of concurrent connections. Quesma has been tested with the following software versions:

SoftwareVersion
Docker24.0.7
Elasticsearch/Kibana8.11.1
ClickHouse24.1, 23.12
ClickHouse Cloud24.5
OpenSearch/OpenSearch Dashboards2.12.0
Hydrolixv4.8.12

DANGER

Quesma supports only ElasticSearch/Kibana 8.0 or above.

ClickHouse limitations

  • When using a cluster deployment of ClickHouse, the tables automatically created by Quesma (during Ingest) will use the MergeTree engine. If you wish to use the ReplicatedMergeTree engine instead, you will have to create the tables manually with ReplicatedMergeTree engine before ingesting data to Quesma.
    • Note: On ClickHouse Cloud, the tables automatically created by Quesma will use the ReplicatedMergeTree engine (ClickHouse Cloud default engine).

Functional limitations

Currently supported:

  • front-end support for Kibana and Open Search Dashboards, limited to Discover(LogExplorer) interface and Dashboard panels
  • read-only back-end support for Elastic/OpenSearch as origin source and ClickHouse or Hydrolix as destination source
  • most popular Query DSL, including: boolean, match, match phrase, multi-match, query string, nested, match all, exists, prefix, range, term, terms, wildcard
  • most popular Aggregations, including: avg, cardinality, max, min, percentile ranks, percentiles, stats, sum, top hits, top metrics, value counts, date histogram, date range, filter, filters, histogram, range, singificant terms, terms

Which as a result allows you to run Kibana/OSD queries and dashboards on data residing in ClickHouse/Hydrolix.

Will be relaxed, but not considered as best practice:

  • Quesma does not allow mixed-data source queries, e.g. calling GET /data_a,data_b/_search where data_a is in Elasticsearch and data_b is ClickHouse table.
    • For Kibana user, this means that Data View cannot contain multiple indices backed up by different data sources.
    • For Elasticsearch API user, this means that you cannot perform queries like GET /data_a,data_b/_search, where data_a is in Elasticsearch and data_b is ClickHouse table.
  • Management API is not supported.

Currently not supported future roadmap items:

  • Some Query DSL features.
  • Some aggregations, esp. those operating on geo_point/geo_shape types
  • Quesma does not support all Elasticsearch API endpoints. Please refer to the List of supported endpoints section for more details.
  • JSON are not pretty printed in the response.
  • The schema support is limited.
    • Elasticsearch types: date, text, keyword, boolean, byte, short, integer, long, unsigned_long, float, half_float, double, ip, geo_point, point
    • Clickhouse types: Date, DateTime, DateTime64, String, FixedString, LowCardinality(String), Bool, UInt8, UInt16, UInt32, UInt64, Int8, Int16, Int32, Int64, Float32, Float64, Array (of types listed in this list).
  • Some advanced query parameters are ignored.
  • No support for SQL, EQL (Event Query Language), PPL, or ES/QL.
  • Better secret support.

Performance limitations

  • A single Quesma container can process 50 concurrent HTTP requests. More requests would receive an HTTP 429 status code.
  • Async results are stored for 15 minutes. Only 10k or 500MB of async results are supported. They are not persisted across restarts.
  • No more than 10,000 result hits.
  • No partial results for long-running queries. All results are returned in one response once full query is finished
  • No efficient support for metrics.

Known bugs

  • Some schema-related endpoints (such as PUT /:index) don't support dual-writes: the request is only handled by the ClickHouse/Hydrolix connector and not forwarded to Elastic. A workaround for this problem is to send the request manually directly to Elastic. The status of the bug is tracked on Quesma's GitHub Issues page.
  • The _count endpoint does not support tables in non-default databases. The status of the bug is tracked on Quesma's GitHub Issues page.

List of supported endpoints

Quesma supports a subset of OpenSearch/Elasticsearch API endpoints. Upon a query, Quesma will forward the request to the appropriate data source (Elasticsearch or ClickHouse). The following endpoints are supported:

  • Search:
    • POST /:index/_search
    • POST /:index/_async_search
    • GET /_async_search/status/:id
    • GET /_async_search/:id, DELETE /_async_search/:id
    • GET /:index/_count
    • POST /:index/_terms_enum
    • GET /:index/_eql/search, POST /:index/_eql/search
  • Schema:
    • GET /:index
    • GET /:index/_mapping, PUT /:index/_mapping
    • PUT /:index
    • POST /:index/_field_caps
    • POST /:index/_terms_enum
    • POST /:index
    • GET /:index/_field_caps, POST /:index/_field_caps
    • GET /_resolve/index/:index
  • Ingest:
    • POST /_bulk, PUT /_bulk
    • POST /:index/_bulk
    • POST /:index/_doc
  • Administrative:
    • GET /_cluster/health
    • POST /:index/_refresh

Warning: Quesma does not support path parameters in URLs listed above.

List of supported Kibana features

Quesma allows querying data from Kibana or OpenSearch Dashboard, but not all features are supported.

For querying data, users can use:

Additional features:

  • Alerting (ref: Kibana docs) - limited to Elasticsearch query (KQL or Lucene and Query DSL) types