DBMS > Microsoft SQL Server vs. Netezza vs. RocksDB vs. Splice Machine vs. Splunk

System Properties Comparison Microsoft SQL Server vs. Netezza vs. RocksDB vs. Splice Machine vs. Splunk

Editorial information provided by DB-Engines

Name

Description

Microsofts flagship relational DBMS

Data warehouse and analytics appliance part of IBM PureSystems

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

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

Analytics Platform for Big Data

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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Trend Chart

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Score	7.56
Rank	#48	Overall
	#31	Relational DBMS

Score	2.84
Rank	#97	Overall
	#16	Key-value stores

Score	0.54
Rank	#244	Overall
	#114	Relational DBMS

Score	93.02
Rank	#13	Overall
	#2	Search engines

Website

www.microsoft.com/en-us/sql-server

www.ibm.com/products/netezza

rocksdb.org

splicemachine.com

www.splunk.com

Technical documentation

learn.microsoft.com/en-US/sql/sql-server

github.com/facebook/rocksdb/wiki

splicemachine.com/how-it-works

docs.splunk.com/Documentation/Splunk

Developer

Microsoft

IBM

Facebook, Inc.

Splice Machine

Splunk Inc.

Initial release

1989

2000

2013

2014

2003

Current release

SQL Server 2022, November 2022

9.4.0, June 2024

3.1, March 2021

License

Commercial or Open Source

commercial

restricted free version is available

commercial

Open Source

BSD

Open Source

AGPL 3.0, commercial license available

commercial

Limited free edition and free developer edition available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

Server operating systems

Linux
Windows

Linux

included in appliance

Linux

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

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

Splunk Search Processing Language for search commands

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

JDBC
ODBC
OLE DB

C++ API
Java API

JDBC
Native Spark Datasource
ODBC

HTTP REST

Supported programming languages

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

C
C++
Fortran
Java
Lua
Perl
Python
R

C
C++
Go
Java
Perl
Python
Ruby

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

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes

Java

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

horizontal partitioning

Shared Nothhing Auto-Sharding, Columnar Partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, but depending on the SQL-Server Edition

Source-replica replication

yes

Multi-source replication
Source-replica replication

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Yes, via Full Spark Integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

ACID

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

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

Users with fine-grained authorization concept

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

Access rights for users and roles

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