DBMS > Apache Phoenix vs. Datomic vs. Drizzle vs. H2

System Properties Comparison Apache Phoenix vs. Datomic vs. Drizzle vs. H2

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

A scale-out RDBMS with evolutionary schema built on Apache HBase

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

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

Primary database model

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	2.06
Rank	#123	Overall
	#58	Relational DBMS

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Website

phoenix.apache.org

www.datomic.com

www.h2database.com

Technical documentation

phoenix.apache.org

docs.datomic.com

www.h2database.com/html/main.html

Developer

Apache Software Foundation

Cognitect

Drizzle project, originally started by Brian Aker

Thomas Mueller

Initial release

2014

2012

2008

2005

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

1.0.7075, December 2023

7.2.4, September 2012

2.2.220, July 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

limited edition free

Open Source

GNU GPL

Open Source

dual-licence (Mozilla public license, Eclipse public 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

Java, Clojure

C++

Java

Server operating systems

Linux
Unix
Windows

All OS with a Java VM

FreeBSD
Linux
OS X

All OS with a Java VM

Data scheme

yes

late-bound, schema-on-read capabilities

yes

Typing

predefined data types such as float or date

yes

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

SQL

Support of SQL

yes

with proprietary extensions

yes

APIs and other access methods

JDBC

RESTful HTTP API

JDBC

JDBC
ODBC

Supported programming languages

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

Clojure
Java

C
C++
Java
PHP

Java

Server-side scripts

Stored procedures

user defined functions

yes

Transaction Functions

Java Stored Procedures and User-Defined Functions

Triggers

By using transaction functions

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

But extensive use of caching in the application peers

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

But extensive use of caching in the application peers

Multi-source replication
Source-replica replication

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

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

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)

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

yes

User concepts

Access control

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

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Recent citations in the news

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2 June 2016, AWS Blog

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