Skip to content
Agentmart
Submit a tool

Elasticsearch

Elasticsearch as a vector database, combining vector search with hybrid lexical search, filters and reranking.

Infrastructure by Elastic

IndexedLicense unknown★ 78,359
Write a review

Chalk Labs

Need help deploying Elasticsearch?

Chalk Labs sets up agents like this inside real teams: connected to your tools, tested on your data, with a human in the loop where it matters.

Book a call

Install

Pick your client. Read the repository before you give any tool access to your data.

pip install elasticsearch

Get the weekly diff

The weekly diff: one email a week with new agent tools, notable updates and grade changes, plus security alerts for tools you follow. Double opt-in, one-click unsubscribe.

We use your email only for this newsletter. Privacy

About

Elasticsearch functions as a vector database, storing embeddings and running kNN similarity search alongside full-text search, filters and aggregations in one engine. It supports dense and sparse vectors and offers a managed semantic_text workflow.

Use cases: knowledge-base, database-access

No reviews yet. Installed it? Reviews come from verified installers only. How reviews work

Fact sheet

Category
Vector databases · search engine
Self-host
Yeselastic.co
SLA
99.95% monthly uptime SLA (Platinum and Enterprise tiers)elastic.co

Plans

HostedContact salesresource-based pricing, pay as you go or prepaid
ServerlessContact salesusage-based pricing, pay as you go or prepaid
Self-managedContact saleslicense-based, by number of nodes and RAM used

From the vendor's pricing page, read Oct 24, 2026.

Facts read from the vendor's own pages by claude-haiku-5-5 on Oct 24, 2026; a fact is shown only with the page it came from.

Signals

Stars
78,359
Forks
26,097
Open issues
4,767
Last commit
Oct 24, 2026 (6 days ago)
Last release
Oct 6, 2026 (24 days ago)

From GitHub (fetched Oct 24, 2026).

Details

Packages
pypi elasticsearchnpm @elastic/elasticsearch
License
License unknown
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

More from Elastic

Done for you

Rather not set it up yourself?

Chalk Labs scopes, builds and runs agents for your team: the task audit, the eval harness, the integrations and the weekly ops report. Fixed scope, priced before we start.

See how we build AI agents →Read the case studies

Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.

launches shipped
50+
launches shipped
media placements
500+
media placements
founders on every account
2
founders on every account

Press we've placed: Forbes · CoinDesk · Decrypt · Cointelegraph · The Block

Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.

Get Elasticsearch running in your business

Tell us what you want to automate. A founder replies within one working day with a plan, not a pitch deck.

Goes to the Chalk Labs founders, not the newsletter. Privacy

Need help deploying Elasticsearch?

CallGet help
Cite this page

Elasticsearch. Agent Mart. https://agentmart.dev/infrastructure/elasticsearch (last updated 2026-10-24)