DBMS > AnzoGraph DB vs. HBase vs. Ingres vs. RocksDB vs. SQream DB

System Properties Comparison AnzoGraph DB vs. HBase vs. Ingres vs. RocksDB vs. SQream 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

Wide-column store based on Apache Hadoop and on concepts of BigTable

Well established RDBMS

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

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

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	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	4.11
Rank	#81	Overall
	#44	Relational DBMS

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

Score	0.70
Rank	#227	Overall
	#104	Relational DBMS

Website

cambridgesemantics.com/anzograph

hbase.apache.org

www.actian.com/databases/ingres

rocksdb.org

sqream.com

Technical documentation

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

hbase.apache.org/book.html

docs.actian.com/ingres

github.com/facebook/rocksdb/wiki

docs.sqream.com

Developer

Cambridge Semantics

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Actian Corporation

Facebook, Inc.

SQream Technologies

Initial release

2018

2008

1974

originally developed at University Berkely in early 1970s

2013

2017

Current release

2.3, January 2021

2.3.4, January 2021

11.2, May 2022

9.2.1, May 2024

2022.1.6, December 2022

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache version 2

commercial

Open Source

BSD

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

C++, CUDA, Haskell, Java, Scala

Server operating systems

Linux

Linux
Unix
Windows

using Cygwin

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Linux

Data scheme

Schema-free and OWL/RDFS-schema support

schema-free, schema definition possible

yes

schema-free

yes

Typing

predefined data types such as float or date

options to bring your own types, AVRO

yes

yes, ANSI Standard SQL Types

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.

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

APIs and other access methods

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

Java API
RESTful HTTP API
Thrift

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

C++ API
Java API

.Net
JDBC
ODBC

Supported programming languages

C++
Java
Python

C
C#
C++
Groovy
Java
PHP
Python
Scala

C
C++
Go
Java
Perl
Python
Ruby

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

Coprocessors in Java

yes

user defined functions in Python

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

horizontal partitioning

Ingres Star to access multiple databases simultaneously

horizontal partitioning

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Multi-source replication
Source-replica replication

Ingres Replicator

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Immediate Consistency or Eventual Consistency

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

Single row ACID (across millions of columns)

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

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

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

fine grained access rights according to SQL-standard

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