DBMS > JanusGraph vs. Netezza vs. RocksDB vs. Splice Machine vs. Splunk

System Properties Comparison JanusGraph vs. Netezza vs. RocksDB vs. Splice Machine vs. Splunk

Editorial information provided by DB-Engines

Name

Description

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

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

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

Score	2.02
Rank	#125	Overall
	#12	Graph DBMS

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Score	89.10
Rank	#14	Overall
	#2	Search engines

Website

janusgraph.org

www.ibm.com/products/netezza

rocksdb.org

splicemachine.com

www.splunk.com

Technical documentation

docs.janusgraph.org

github.com/facebook/rocksdb/wiki

splicemachine.com/how-it-works

docs.splunk.com/Documentation/Splunk

Developer

Linux Foundation; originally developed as Titan by Aurelius

IBM

Facebook, Inc.

Splice Machine

Splunk Inc.

Initial release

2017

2000

2013

2014

2003

Current release

0.6.3, February 2023

9.2.1, May 2024

3.1, March 2021

License

Commercial or Open Source

Open Source

Apache 2.0

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

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

Implementation language

Java

C++

Java

Server operating systems

Linux
OS X
Unix
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

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

JDBC
ODBC
OLE DB

C++ API
Java API

JDBC
Native Spark Datasource
ODBC

HTTP REST

Supported programming languages

Clojure
Java
Python

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

yes

Java

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding

horizontal partitioning

Shared Nothhing Auto-Sharding, Columnar Partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes

Multi-source replication
Source-replica replication

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

yes

Yes, via Full Spark Integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

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

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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

User authentification and security via Rexster Graph Server

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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