DBMS > Blazegraph vs. Datomic vs. InterSystems Caché vs. RocksDB vs. SingleStore

System Properties Comparison Blazegraph vs. Datomic vs. InterSystems Caché vs. RocksDB vs. SingleStore

Editorial information provided by DB-Engines

Name

Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.

Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.

Description

High-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.

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

A multi-model DBMS and application server

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

MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type

Primary database model

Graph DBMS
RDF store

Relational DBMS

Key-value store
Object oriented DBMS
Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Document store

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

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

Score	0.75
Rank	#219	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

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

Score	5.60
Rank	#62	Overall
	#35	Relational DBMS

Website

blazegraph.com

www.datomic.com

www.intersystems.com/products/cache

rocksdb.org

www.singlestore.com

Technical documentation

wiki.blazegraph.com

docs.datomic.com

docs.intersystems.com

github.com/facebook/rocksdb/wiki

docs.singlestore.com

Developer

Blazegraph

Cognitect

InterSystems

Facebook, Inc.

SingleStore Inc.

Initial release

2006

2012

1997

2013

Current release

2.1.5, March 2019

1.0.6735, June 2023

2018.1.4, May 2020

8.11.4, April 2024

8.5, January 2024

License

Commercial or Open Source

Open Source

extended commercial license available

commercial

limited edition free

commercial

Open Source

BSD

commercial

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.

SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities

Implementation language

Java

Java, Clojure

C++

C++, Go

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows

Linux

64 bit version required

Data scheme

schema-free

yes

depending on used data model

schema-free

yes

Typing

predefined data types such as float or date

yes

RDF literal types

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

SPARQL is used as query language

yes

but no triggers and foreign keys

APIs and other access methods

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

RESTful HTTP API

.NET Client API
JDBC
ODBC
RESTful HTTP API

C++ API
Java API

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

Supported programming languages

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

Clojure
Java

C#
C++
Java

C
C++
Go
Java
Perl
Python
Ruby

Bash
C
C#
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

But extensive use of caching in the application peers

none

horizontal partitioning

Sharding

hash partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

But extensive use of caching in the application peers

Source-replica replication

yes

Source-replica replication

stores two copies of each physical data partition on two separate nodes

MapReduce

Offers an API for user-defined Map/Reduce methods

can define user-defined aggregate functions for map-reduce-style calculations

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate 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

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

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

yes

All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.

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

Security and Authentication via Web Application Container (Tomcat, Jetty)

Access rights for users, groups and roles

Fine grained access control via users, groups and roles

More information provided by the system vendor

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Market metrics

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Licensing and pricing models

F ree Tier and Enterprise Edition
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