DBMS > AnzoGraph DB vs. Infobright vs. Kinetica vs. RocksDB

System Properties Comparison AnzoGraph DB vs. Infobright vs. Kinetica vs. RocksDB

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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

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Fully vectorized database across both GPUs and CPUs

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

Primary database model

Graph DBMS
RDF store

Relational DBMS

Key-value store

Secondary database models

Spatial DBMS
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	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

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

Website

cambridgesemantics.com/anzograph

ignitetech.com/softwarelibrary/infobrightdb

www.kinetica.com

rocksdb.org

Technical documentation

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

docs.kinetica.com

github.com/facebook/rocksdb/wiki

Developer

Cambridge Semantics

Ignite Technologies Inc.; formerly InfoBright Inc.

Kinetica

Facebook, Inc.

Initial release

2018

2005

2012

2013

Current release

2.3, January 2021

7.1, August 2021

8.11.4, April 2024

License

Commercial or Open Source

commercial

free trial version available

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

commercial

Open Source

BSD

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

C, C++

C++

Server operating systems

Linux

Linux
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.

Secondary indexes

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

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

yes

SQL-like DML and DDL statements

APIs and other access methods

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

ADO.NET
JDBC
ODBC

JDBC
ODBC
RESTful HTTP API

C++ API
Java API

Supported programming languages

C++
Java
Python

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C++
Java
JavaScript (Node.js)
Python

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions and aggregates

user defined functions

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

not needed in graphs

yes

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

In-memory capabilities

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

yes

GPU vRAM or System RAM

yes

User concepts

Access control

Access rights for users and roles

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

Access rights for users and roles on table level

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