IBM Databases for Elasticsearch

Support infrastructure monitoring and security analytics

IBM Cloud Databases for Elasticsearch is a fully managed Elasticsearch Service offering on IBM Cloud. It combines the flexibility of a semantic search engine with the indexing power of a JSON document database and Vector DB capabilities via a number of built-in features.

Severless scaling

IBM Cloud Databases for Elasticsearch allows you to scale disk and RAM independently to best fit your application requirements.

Open source compatible

The service is compatible with Elasticsearch APIs, data formats and clients. Applications that already leverage Elasticsearch can use IBM Cloud Databases for Elasticsearch as a drop-in replacement.

Machine learning to cut through data noise

Get immediate value from machine learning with all the powerful out-of-the-box features of Elasticsearch. Make your enterprise data work harder with Elastic’s machine learning algorithms, specialist machine learning nodes and semantic search.

Automation aware

Get to global scale with integrated, infrastructure-as-code tools, such as IBM Cloud Schematics with Terraform and Red Hat® Ansible® support at no additional charge.

Use cases

Machine learning
Machine learning
Machine learning
Vector embeddings
Vector embeddings
Log analysis
Log analysis

Generative AI - RAG pattern and integration with third party Machine Learning Models

Integrate with Large Language Models and Machine Learning Models (already existing or bring your own) to provide core machine learning capabilities such as Retrieval Augmented Generation (RAG) for conversational search, entity recognition or insight extraction. IBM Watson portfolio using these capabilities are watsonx.Assistant, watsonx.Orchestrate and Watsonx.ai.

Vector embeddings and semantic search

Store vector representations and enable advanced operations such as similarity searches, content retrieval, natural language processing, recommendation systems or anomaly detection.

Log analysis

Analyze and visualize logs and machine-generated data from servers, sensors and websites to debug applications and systems.

Generative AI - RAG pattern and integration with third party Machine Learning Models

Vector embeddings and semantic search

Store vector representations and enable advanced operations such as similarity searches, content retrieval, natural language processing, recommendation systems or anomaly detection.

Log analysis

Analyze and visualize logs and machine-generated data from servers, sensors and websites to debug applications and systems.

Resources

IBM Cloud professional training

Build your monitoring and incident management skills through log courses contained within the IBM Cloud Professional Site Reliability Engineer (SRE) curriculum.

Explore IBM training

Review product documentation

Get started with IBM Cloud Databases for Elastisearch. Follow easy steps to manage user access, provision an instance, collect metrics and launch the web UI.

Get started with Databases for Elasticsearch

IBM Cloud PaaS User Community

Access IBM Cloud Databases experts, IT ops managers, solution architects, SREs and other professionals in the industry and join the conversation.

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IBM Cloud Databases for PostgreSQL

Managed PostgreSQL, built enterprise-ready, with native integration into the IBM Cloud

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