DBMS > IBM Db2 warehouse vs. Sequoiadb vs. Spark SQL vs. Splunk vs. Transbase

System Properties Comparison IBM Db2 warehouse vs. Sequoiadb vs. Spark SQL vs. Splunk vs. Transbase

Editorial information provided by DB-Engines

Name

Description

Cloud-based data warehousing service

NewSQL database with distributed OLTP and SQL

Spark SQL is a component on top of 'Spark Core' for structured data processing

Analytics Platform for Big Data

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Relational DBMS

Document store
Relational DBMS

Relational DBMS

Search engine

Relational DBMS

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

Score	1.37
Rank	#160	Overall
	#74	Relational DBMS

Score	0.50
Rank	#258	Overall
	#41	Document stores
	#120	Relational DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	89.10
Rank	#14	Overall
	#2	Search engines

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Website

www.ibm.com/products/db2/warehouse

www.sequoiadb.com

spark.apache.org/sql

www.splunk.com

www.transaction.de/en/products/transbase.html

Technical documentation

www.sequoiadb.com/en/index.php?m=Files&a=index

spark.apache.org/docs/latest/sql-programming-guide.html

docs.splunk.com/Documentation/Splunk

www.transaction.de/en/products/transbase/features.html

Developer

IBM

Sequoiadb Ltd.

Apache Software Foundation

Splunk Inc.

Transaction Software GmbH

Initial release

2014

2013

2014

2003

1987

Current release

3.5.0 ( 2.13), September 2023

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

Open Source

Server: AGPL; Client: Apache V2

Open Source

Apache 2.0

commercial

Limited free edition and free developer edition available

commercial

free development license

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++

Scala

C and C++

Server operating systems

hosted

Linux

Linux
OS X
Windows

Linux
OS X
Solaris
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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

SQL-like query language

SQL-like DML and DDL statements

Splunk Search Processing Language for search commands

yes

APIs and other access methods

.NET Client API
JDBC
ODBC
OLE DB

proprietary protocol using JSON

JDBC
ODBC

HTTP REST

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

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

.Net
C++
Java
PHP
Python

Java
Python
R
Scala

C#
Java
JavaScript
PHP
Python
Ruby

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

PL/SQL, SQL PL

JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes, utilizing Spark Core

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

none

Multi-source replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

Document is locked during a transaction

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

yes

Concurrency

Support for concurrent manipulation of data

yes

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

simple password-based access control

Access rights for users and roles

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

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