DBMS > IBM Db2 warehouse vs. Percona Server for MySQL vs. Splice Machine

System Properties Comparison IBM Db2 warehouse vs. Percona Server for MySQL vs. Splice Machine

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Editorial information provided by DB-Engines

Name

Description

Cloud-based data warehousing service

Enhanced drop-in replacement for MySQL based on XtraDB or TokuDB storage engines with improved performance and additional diagnostic and management features.

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

Primary database model

Relational DBMS

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

Score	1.34
Rank	#166	Overall
	#76	Relational DBMS

Score	2.21
Rank	#121	Overall
	#58	Relational DBMS

Score	0.54
Rank	#255	Overall
	#116	Relational DBMS

Website

www.ibm.com/products/db2/warehouse

www.percona.com/software/mysql-database/percona-server

splicemachine.com

Technical documentation

www.percona.com/downloads/Percona-Server-LATEST

splicemachine.com/how-it-works

Developer

IBM

Percona

Splice Machine

Initial release

2014

2008

2014

Current release

8.0.36-28, 2024

3.1, March 2021

License

Commercial or Open Source

commercial

Open Source

GPL version 2

Open Source

AGPL 3.0, commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C and C++

Java

Server operating systems

hosted

Linux

Linux
OS X
Solaris
Windows

Data scheme

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.

Import/export of XML data possible

yes

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

.NET Client API
JDBC
ODBC
OLE DB

ADO.NET
JDBC
ODBC

JDBC
Native Spark Datasource
ODBC

Supported programming languages

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

Ada
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

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

Server-side scripts

Stored procedures

PL/SQL, SQL PL

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication
XtraDB Cluster

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

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

Users with fine-grained authorization concept

no user groups or roles

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

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More resources

Recent citations in the news

Announcing the deprecation of prior generation Db2 Warehouse plans on AWS
16 October 2023, ibm.com

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31 May 2023, Datamation

Db2 Warehouse delivers 4x faster query performance than previously, while cutting storage costs by 34x
11 July 2023, ibm.com

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24 February 2023, TechRepublic

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5 August 2020, Blocks and Files

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

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19 January 2021, PR Newswire

Splice Machine Launches Feature Store to Simplify Feature Engineering
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18 September 2019, Towards Data Science

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