DBMS > Datomic vs. Drizzle vs. Hypertable vs. Oracle NoSQL

System Properties Comparison Datomic vs. Drizzle vs. Hypertable vs. Oracle NoSQL

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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.

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

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.

An open source BigTable implementation based on distributed file systems such as Hadoop

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Primary database model

Relational DBMS

Wide column store

Document store
Key-value store
Relational DBMS

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

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Website

www.datomic.com

www.oracle.com/database/nosql/technologies/nosql

Technical documentation

docs.datomic.com

docs.oracle.com/en/database/other-databases/nosql-database/index.html

Developer

Cognitect

Drizzle project, originally started by Brian Aker

Hypertable Inc.

Oracle

Initial release

2012

2008

2009

2011

Current release

1.0.6735, June 2023

7.2.4, September 2012

0.9.8.11, March 2016

23.3, December 2023

License

Commercial or Open Source

commercial

limited edition free

Open Source

GNU GPL

Open Source

GNU version 3. Commercial license available

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

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

C++

Java

Server operating systems

All OS with a Java VM

FreeBSD
Linux
OS X

Linux
OS X
Windows

an inofficial Windows port is available

Linux
Solaris SPARC/x86

Data scheme

yes

schema-free

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

Typing

predefined data types such as float or date

yes

optional

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

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

yes

with proprietary extensions

SQL-like DML and DDL statements

APIs and other access methods

RESTful HTTP API

JDBC

C++ API
Thrift

RESTful HTTP API

Supported programming languages

Clojure
Java

C
C++
Java
PHP

C++
Java
Perl
PHP
Python
Ruby

C
C#
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Transaction Functions

Triggers

By using transaction functions

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

Multi-source replication
Source-replica replication

selectable replication factor on file system level

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

configurable

ACID within a storage node (=shard)

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

off heap cache

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights for users and roles

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