DBMS > H2 vs. IBM Db2 Event Store vs. Solr vs. TerarkDB

System Properties Comparison H2 vs. IBM Db2 Event Store vs. Solr vs. TerarkDB

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Editorial information provided by DB-Engines

Name

Description

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

Distributed Event Store optimized for Internet of Things use cases

A widely used distributed, scalable search engine based on Apache Lucene

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Relational DBMS

Event Store
Time Series DBMS

Search engine

Key-value store

Secondary database models

Spatial DBMS

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

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	42.91
Rank	#24	Overall
	#3	Search engines

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

www.h2database.com

www.ibm.com/products/db2-event-store

solr.apache.org

github.com/bytedance/terarkdb

Technical documentation

www.h2database.com/html/main.html

www.ibm.com/docs/en/db2-event-store

solr.apache.org/resources.html

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Thomas Mueller

IBM

Apache Software Foundation

ByteDance, originally Terark

Initial release

2005

2017

2006

2016

Current release

2.2.220, July 2023

2.0

9.6.0, April 2024

License

Commercial or Open Source

Open Source

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

commercial

free developer edition available

Open Source

Apache Version 2

commercial

restricted open source version available

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

C and C++

Java

C++

Server operating systems

All OS with a Java VM

Linux

Linux, macOS, Windows for the developer addition

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Data scheme

yes

Dynamic Fields enables on-the-fly addition of new fields

schema-free

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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

Secondary indexes

yes

All search fields are automatically indexed

SQL

Support of SQL

yes

through the embedded Spark runtime

Solr Parallel SQL Interface

APIs and other access methods

JDBC
ODBC

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

Java API
RESTful HTTP/JSON API

C++ API
Java API

Supported programming languages

Java

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

C++
Java

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

yes

Java plugins

Triggers

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

Active-active shard replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

No - written data is immutable

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

yes

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes

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