DBMS > AgensGraph vs. GigaSpaces vs. JanusGraph vs. RocksDB vs. Splunk

System Properties Comparison AgensGraph vs. GigaSpaces vs. JanusGraph vs. RocksDB vs. Splunk

Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

A Graph DBMS optimized for distributed clusters

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

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

Analytics Platform for Big Data

Primary database model

Graph DBMS
Relational DBMS

Document store
Object oriented DBMS

Values are user defined objects

Graph DBMS

Key-value store

Search engine

Secondary database models

Graph DBMS
Search engine

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

Score	0.20
Rank	#321	Overall
	#27	Graph DBMS
	#143	Relational DBMS

Score	0.97
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	86.45
Rank	#14	Overall
	#2	Search engines

Website

bitnine.net/agensgraph

Technical documentation

bitnine.net/documentation

docs.gigaspaces.com/latest/landing.html

docs.janusgraph.org

github.com/facebook/rocksdb/wiki

docs.splunk.com/Documentation/Splunk

Developer

Bitnine Global Inc.

Gigaspaces Technologies

Linux Foundation; originally developed as Titan by Aurelius

Facebook, Inc.

Splunk Inc.

Initial release

2016

2000

2017

2013

2003

Current release

2.1, December 2018

15.5, September 2020

0.6.3, February 2023

8.11.4, April 2024

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

Apache Version 2; Commercial licenses available

Open Source

Apache 2.0

Open Source

BSD

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++, .Net

Java

C++

Server operating systems

Linux
OS X
Windows

Linux
macOS
Solaris
Windows

Linux
OS X
Unix
Windows

Linux

Linux
OS X
Solaris
Windows

Data scheme

depending on used data model

schema-free

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.

XML can be used for describing objects metadata

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-99 for query and DML statements

Splunk Search Processing Language for search commands

APIs and other access methods

Cypher Query Language
JDBC

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

C++ API
Java API

HTTP REST

Supported programming languages

C
Java
JavaScript
Python

.Net
C++
Java
Python
Scala

Clojure
Java
Python

C
C++
Go
Java
Perl
Python
Ruby

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes, event driven architecture

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

yes

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

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

yes

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

yes

via Faunus, a graph analytics engine

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Eventual Consistency
Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

yes

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

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

fine grained access rights according to SQL-standard

Role-based access control

User authentification and security via Rexster Graph Server

Access rights for users and roles

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