DBMS > AnzoGraph DB vs. Datomic vs. GigaSpaces vs. RocksDB vs. SWC-DB

System Properties Comparison AnzoGraph DB vs. Datomic vs. GigaSpaces vs. RocksDB vs. SWC-DB

Editorial information provided by DB-Engines

Name

Description

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

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

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

A high performance, scalable Wide Column DBMS

Primary database model

Graph DBMS
RDF store

Relational DBMS

Document store
Object oriented DBMS

Values are user defined objects

Key-value store

Wide column store

Secondary database models

Graph DBMS
Search engine

Time Series DBMS

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

Score	0.23
Rank	#307	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

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

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

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

cambridgesemantics.com/anzograph

www.datomic.com

www.gigaspaces.com

rocksdb.org

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

docs.datomic.com

docs.gigaspaces.com/latest/landing.html

github.com/facebook/rocksdb/wiki

Developer

Cambridge Semantics

Cognitect

Gigaspaces Technologies

Facebook, Inc.

Alex Kashirin

Initial release

2018

2012

2000

2013

2020

Current release

2.3, January 2021

1.0.6735, June 2023

15.5, September 2020

8.11.4, April 2024

0.5, April 2021

License

Commercial or Open Source

commercial

free trial version available

commercial

limited edition free

Open Source

Apache Version 2; Commercial licenses available

Open Source

BSD

Open Source

GPL V3

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, Clojure

Java, C++, .Net

C++

Server operating systems

Linux

All OS with a Java VM

Linux
macOS
Solaris
Windows

Linux

Data scheme

Schema-free and OWL/RDFS-schema support

yes

schema-free

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

Secondary indexes

yes

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

SQL-99 for query and DML statements

SQL-like query language

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

RESTful HTTP API

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

C++ API
Java API

Proprietary protocol
Thrift

Supported programming languages

C++
Java
Python

Clojure
Java

.Net
C++
Java
Python
Scala

C
C++
Go
Java
Perl
Python
Ruby

C++

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

Transaction Functions

yes

Triggers

By using transaction functions

yes, event driven architecture

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

none

But extensive use of caching in the application peers

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

none

But extensive use of caching in the application peers

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

recommended only for testing and development

yes

User concepts

Access control

Access rights for users and roles

Role-based access control

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