DBMS > Elasticsearch vs. H2 vs. XTDB

System Properties Comparison Elasticsearch vs. H2 vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Search engine

Relational DBMS

Document store

Secondary database models

Document store
Spatial DBMS
Vector DBMS

Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	135.35
Rank	#7	Overall
	#1	Search engines

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

www.elastic.co/elasticsearch

www.h2database.com

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

www.h2database.com/html/main.html

www.xtdb.com/docs

Developer

Elastic

Thomas Mueller

Juxt Ltd.

Initial release

2010

2005

2019

Current release

8.6, January 2023

2.2.220, July 2023

1.19, September 2021

License

Commercial or Open Source

Open Source

Elastic License

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

MIT License

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Clojure

Server operating systems

All OS with a Java VM

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free

Flexible type definitions. Once a type is defined, it is persistent

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

Java API
RESTful HTTP/JSON API

JDBC
ODBC

HTTP REST
JDBC

Supported programming languages

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

Java

Clojure
Java

Server-side scripts

Stored procedures

yes

Java Stored Procedures and User-Defined Functions

Triggers

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

With clustering: 2 database servers on different computers operate on identical copies of a database

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

Memcached and Redis integration

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2017
2 January 2018, Paul Andlinger, Matthias Gelbmann

Elasticsearch moved into the top 10 most popular database management systems
3 July 2017, Matthias Gelbmann

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

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Recent citations in the news

Netflix Uses Elasticsearch Percolate Queries to Implement Reverse Searches Efficiently
29 April 2024, InfoQ.com

Using Elasticsearch to Offload Search and Analytics from DynamoDB: Pros and Cons
10 May 2024, hackernoon.com

Splunk vs Elasticsearch | A Comparison and How to Choose
12 January 2024, SentinelOne

The Total Economic Impact™️ of Elasticsearch
8 May 2024, BankInfoSecurity.com

Introducing Elasticsearch Vector Database to Azure OpenAI Service On Your Data (Preview)
26 March 2024, insider.govtech.com

provided by Google News

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