DBMS > AnzoGraph DB vs. EDB Postgres vs. Ingres vs. RocksDB

System Properties Comparison AnzoGraph DB vs. EDB Postgres vs. Ingres 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

The EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.

Well established RDBMS

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

Document store
Spatial 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	1.90
Rank	#135	Overall
	#63	Relational DBMS

Score	4.11
Rank	#81	Overall
	#44	Relational DBMS

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

Website

cambridgesemantics.com/anzograph

www.enterprisedb.com

www.actian.com/databases/ingres

rocksdb.org

Technical documentation

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

www.enterprisedb.com/docs

docs.actian.com/ingres

github.com/facebook/rocksdb/wiki

Developer

Cambridge Semantics

EnterpriseDB

Actian Corporation

Facebook, Inc.

Initial release

2018

2005

1974

originally developed at University Berkely in early 1970s

2013

Current release

2.3, January 2021

14, December 2021

11.2, May 2022

8.11.4, April 2024

License

Commercial or Open Source

commercial

free trial version available

commercial

BSD for PostgreSQL-components

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++

Server operating systems

Linux

Linux
Windows

AIX
HP Open VMS
HP-UX
Linux
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.

yes

specific XML-type available, but no XML query functionality.

but tools for importing/exporting data from/to XML-files available

Secondary indexes

yes

SQL

Support of SQL

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

yes

standard with numerous extensions

yes

APIs and other access methods

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

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

C++ API
Java API

Supported programming languages

C++
Java
Python

.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions and aggregates

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

horizontal partitioning

by hash, list or range

horizontal partitioning

Ingres Star to access multiple databases simultaneously

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Multi-source replication

Ingres Replicator

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

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

yes, multi-version concurrency control (MVCC)

yes

MVCC

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

User concepts

Access control

Access rights for users and roles

fine grained access rights according to SQL-standard

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