DBMS > H2 vs. OpenQM vs. SAP SQL Anywhere vs. Splice Machine

System Properties Comparison H2 vs. OpenQM vs. SAP SQL Anywhere vs. Splice Machine

Please select another system to include it in the comparison.

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.

QpenQM is a high-performance, self-tuning, multi-value DBMS

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

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

Primary database model

Relational DBMS

Multivalue DBMS

Relational DBMS

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	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Website

www.h2database.com

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

www.sap.com/products/technology-platform/sql-anywhere.html

splicemachine.com

Technical documentation

www.h2database.com/html/main.html

help.sap.com/docs/SAP_SQL_Anywhere

splicemachine.com/how-it-works

Developer

Thomas Mueller

Rocket Software, originally Martin Phillips

SAP

formerly Sybase

Splice Machine

Initial release

2005

1993

1992

2014

Current release

2.2.220, July 2023

3.4-12

17, July 2015

3.1, March 2021

License

Commercial or Open Source

Open Source

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

Open Source

GPLv2, extended commercial license available

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

Java

Server operating systems

All OS with a Java VM

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

Linux
OS X
Solaris
Windows

Data scheme

yes

with some exceptions

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

JDBC
ODBC

ADO.NET
HTTP API
JDBC
ODBC

JDBC
Native Spark Datasource
ODBC

Supported programming languages

Java

.Net
Basic
C
Java
Objective C
PHP
Python

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

yes

yes, in C/C++, Java, .Net or Perl

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

none

Shared Nothhing Auto-Sharding, Columnar Partitioning

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

Source-replica replication

Database mirroring

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

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

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

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

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

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

SAP vulnerabilities Let Attacker Inject OS Commands—Patch Now!
11 July 2023, CybersecurityNews

SAP Again Named a Leader in 2021 Gartner® Magic Quadrant™ for Cloud Database Management Systems
16 December 2021, SAP News

SAP launches HANA cloud platform, partners with Siemens, Intel
6 May 2015, Channel Daily News

AWS, IBM, Microsoft, Google emerge Cloud DBMS leaders
22 December 2022, Daily Host News

provided by Google News

Machine learning data pipeline outfit Splice Machine files for insolvency
26 August 2021, The Register

Splice Machine Launches the Splice Machine Feature Store to Simplify Feature Engineering and Democratize Machine ...
19 January 2021, PR Newswire

Splice Machine Launches Feature Store to Simplify Feature Engineering
19 January 2021, Datanami

Distributed SQL System Review: Snowflake vs Splice Machine
18 September 2019, Towards Data Science

Splice Machine takes on big boys of big data with Hadoop RDBMS
21 January 2015, RCR Wireless News

provided by Google News

Share this page