DBMS > H2 vs. Prometheus vs. RocksDB vs. Solr vs. XTDB

System Properties Comparison H2 vs. Prometheus vs. RocksDB vs. Solr vs. XTDB

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.

Open-source Time Series DBMS and monitoring system

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

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

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

Primary database model

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	8.42
Rank	#47	Overall
	#2	Time Series DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	42.91
Rank	#24	Overall
	#3	Search engines

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

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

Technical documentation

www.h2database.com/html/main.html

prometheus.io/docs

github.com/facebook/rocksdb/wiki

solr.apache.org/resources.html

www.xtdb.com/docs

Developer

Thomas Mueller

Facebook, Inc.

Apache Software Foundation

Juxt Ltd.

Initial release

2005

2015

2013

2006

2019

Current release

2.2.220, July 2023

8.11.4, April 2024

9.6.0, April 2024

1.19, September 2021

License

Commercial or Open Source

Open Source

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

Open Source

Apache 2.0

Open Source

BSD

Open Source

Apache Version 2

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

C++

Java

Clojure

Server operating systems

All OS with a Java VM

Linux
Windows

Linux

All OS with a Java VM

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

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

Data scheme

yes

schema-free

yes

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

schema-free

Typing

predefined data types such as float or date

yes

Numeric data only

yes

supports customizable data types and automatic typing

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.

Import of XML data possible

yes

Secondary indexes

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

yes

Solr Parallel SQL Interface

limited SQL, making use of Apache Calcite

APIs and other access methods

JDBC
ODBC

RESTful HTTP/JSON API

C++ API
Java API

Java API
RESTful HTTP/JSON API

HTTP REST
JDBC

Supported programming languages

Java

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

C
C++
Go
Java
Perl
Python
Ruby

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

Clojure
Java

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

Java plugins

Triggers

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

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

yes

by Federation

yes

yes, each node contains all data

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

none

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes

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