DBMS > Drizzle vs. gStore vs. Ingres vs. Splice Machine

System Properties Comparison Drizzle vs. gStore vs. Ingres vs. Splice Machine

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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

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

A native Graph DBMS to store and maintain very large RDF datasets.

Well established RDBMS

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Relational DBMS

Graph DBMS
RDF store

Relational DBMS

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

Score	0.14
Rank	#342	Overall
	#34	Graph DBMS
	#16	RDF stores

Score	3.80
Rank	#82	Overall
	#44	Relational DBMS

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Website

en.gstore.cn

www.actian.com/databases/ingres

splicemachine.com

Technical documentation

en.gstore.cn/#/enDocs

docs.actian.com/ingres

splicemachine.com/how-it-works

Developer

Drizzle project, originally started by Brian Aker

Actian Corporation

Splice Machine

Initial release

2008

2016

1974

originally developed at University Berkely in early 1970s

2014

Current release

7.2.4, September 2012

1.2, November 2023

11.2, May 2022

3.1, March 2021

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

BSD

commercial

Open Source

AGPL 3.0, commercial license 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

C++

Java

Server operating systems

FreeBSD
Linux
OS X

Linux

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free and OWL/RDFS-schema support

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.

but tools for importing/exporting data from/to XML-files available

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

APIs and other access methods

JDBC

HTTP API
SPARQL 1.1

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

JDBC
Native Spark Datasource
ODBC

Supported programming languages

C
C++
Java
PHP

C++
Java
JavaScript (Node.js)
PHP
Python

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

yes

Java

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Ingres Star to access multiple databases simultaneously

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Ingres Replicator

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Users, roles and permissions, Role-Based Access Control (RBAC) supported

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

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More resources

DB-Engines blog posts

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