DBMS > AnzoGraph DB vs. Atos Standard Common Repository vs. Kyligence Enterprise vs. SpaceTime

System Properties Comparison AnzoGraph DB vs. Atos Standard Common Repository vs. Kyligence Enterprise vs. SpaceTime

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

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

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

A distributed analytics engine for big data, built on top of Apache Kylin

SpaceTime is a spatio-temporal DBMS with a focus on performance.

Primary database model

Graph DBMS
RDF store

Document store
Key-value store

Relational DBMS

Spatial DBMS

Secondary database models

Relational 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	0.40
Rank	#269	Overall
	#124	Relational DBMS

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Website

cambridgesemantics.com/anzograph

atos.net/en/convergence-creators/portfolio/standard-common-repository

kyligence.io/kyligence-enterprise

www.mireo.com/spacetime

Technical documentation

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

Developer

Cambridge Semantics

Atos Convergence Creators

Kyligence, Inc.

Mireo

Initial release

2018

2016

2020

Current release

2.3, January 2021

1703

License

Commercial or Open Source

commercial

free trial version available

commercial

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

C++

Server operating systems

Linux

Data scheme

Schema-free and OWL/RDFS-schema support

Schema and schema-less with LDAP views

yes

Typing

predefined data types such as float or date

optional

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 and SPARQL* as primary query language. Cypher preview.

ANSI SQL for queries (using Apache Calcite)

A subset of ANSI SQL is implemented

APIs and other access methods

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

LDAP

JDBC
ODBC
RESTful HTTP API

RESTful HTTP API

Supported programming languages

C++
Java
Python

All languages with LDAP bindings

C#
C++
Python

Server-side scripts

Stored procedures

user defined functions and aggregates

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

cell division

Fixed-grid hypercubes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

yes

Real-time block device replication (DRBD)

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 depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

Transaction concepts

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

ACID

Atomic execution of specific operations

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

User concepts

Access control

Access rights for users and roles

LDAP bind authentication

yes

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

AnzoGraph review: A graph database for deep analytics
15 April 2019, InfoWorld

Cambridge Semantics Fits AnzoGraph DB with More Speed, Free Access
23 January 2020, Solutions Review

AnzoGraph: A W3C Standards-Based Graph Database | by Jo Stichbury
8 February 2019, Towards Data Science

Back to the future: Does graph database success hang on query language?
5 March 2018, ZDNet

Is The Enterprise Knowledge Graph Finally Going To Make All Data Usable?
19 September 2018, Forbes

provided by Google News

Kyligence Grows OLAP Business in the Cloud
20 February 2020, Datanami

Kyligence adds ClickHouse OLAP engine to its analytics platform
10 August 2021, VentureBeat

How Kyligence Cloud uses Amazon EMR Serverless to simplify OLAP | Amazon Web Services
9 November 2022, AWS Blog

Distributed OLAPer Kyligence accelerates core engine, adds real-time data support – Blocks and Files
10 August 2021, Blocks & Files

The 10 Hottest Big Data Tools Of 2023
23 November 2023, CRN

provided by Google News

Share this page