DBMS > Datomic vs. Derby vs. Drizzle vs. Heroic

System Properties Comparison Datomic vs. Derby vs. Drizzle vs. Heroic

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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

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

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

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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Primary database model

Relational DBMS

Time Series DBMS

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

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	4.71
Rank	#69	Overall
	#37	Relational DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Website

www.datomic.com

db.apache.org/derby

github.com/spotify/heroic

Technical documentation

docs.datomic.com

db.apache.org/derby/manuals/index.html

spotify.github.io/heroic

Developer

Cognitect

Apache Software Foundation

Drizzle project, originally started by Brian Aker

Spotify

Initial release

2012

1997

2008

2014

Current release

1.0.6735, June 2023

10.17.1.0, November 2023

7.2.4, September 2012

License

Commercial or Open Source

commercial

limited edition free

Open Source

Apache version 2

Open Source

GNU GPL

Open Source

Apache 2.0

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

Java

C++

Java

Server operating systems

All OS with a Java VM

FreeBSD
Linux
OS X

Data scheme

yes

schema-free

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.

yes

Secondary indexes

yes

via Elasticsearch

SQL

Support of SQL

yes

with proprietary extensions

APIs and other access methods

RESTful HTTP API

JDBC

HQL (Heroic Query Language, a JSON-based language)
HTTP API

Supported programming languages

Clojure
Java

Java

C
C++
Java
PHP

Server-side scripts

Stored procedures

yes

Transaction Functions

Java Stored Procedures

Triggers

By using transaction functions

yes

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

Source-replica replication

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

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

fine grained access rights according to SQL-standard

Pluggable authentication mechanisms

e.g. LDAP, HTTP

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