DBMS > Elasticsearch vs. H2 vs. jBASE vs. PostgreSQL vs. XTDB

System Properties Comparison Elasticsearch vs. H2 vs. jBASE vs. PostgreSQL vs. XTDB

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 robust multi-value DBMS comprising development tools and middleware

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

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

Primary database model

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Document store

Secondary database models

Document store
Spatial DBMS
Vector DBMS

Spatial DBMS

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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	1.41
Rank	#159	Overall
	#3	Multivalue DBMS

Score	645.54
Rank	#4	Overall
	#4	Relational DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

www.elastic.co/elasticsearch

www.h2database.com

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

www.postgresql.org

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

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

www.postgresql.org/docs

www.xtdb.com/docs

Developer

Elastic

Thomas Mueller

Rocket Software (formerly Zumasys)

PostgreSQL Global Development Group

www.postgresql.org/developer

Juxt Ltd.

Initial release

2010

2005

1991

1989

1989: Postgres, 1996: PostgreSQL

2019

Current release

8.6, January 2023

2.2.220, July 2023

5.7

16.3, May 2024

1.19, September 2021

License

Commercial or Open Source

Open Source

Elastic License

Open Source

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

commercial

Open Source

BSD

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.

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Implementation language

Java

Clojure

Server operating systems

All OS with a Java VM

AIX
Linux
Windows

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

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

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

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.

yes

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

Embedded SQL for jBASE in BASIC

yes

standard with numerous extensions

limited SQL, making use of Apache Calcite

APIs and other access methods

Java API
RESTful HTTP/JSON API

JDBC
ODBC

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

HTTP REST
JDBC

Supported programming languages

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

Java

.Net
Basic
Jabbascript
Java

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Clojure
Java

Server-side scripts

Stored procedures

yes

Java Stored Procedures and User-Defined Functions

yes

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Triggers

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

partitioning by range, list and (since PostgreSQL 11) by hash

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

Source-replica replication

other methods possible by using 3rd party extensions

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

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

More information provided by the system vendor

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