DBMS > AnzoGraph DB vs. EsgynDB vs. GeoSpock vs. ITTIA vs. Riak KV

System Properties Comparison AnzoGraph DB vs. EsgynDB vs. GeoSpock vs. ITTIA vs. Riak KV

Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded 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

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Spatial and temporal data processing engine for extreme data scale

Edge Time Series DBMS with Real-Time Stream Processing

Distributed, fault tolerant key-value store

Primary database model

with links between data sets and object tags for the creation of secondary indexes

Secondary database models

Time Series DBMS

Relational DBMS

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

Score	0.29
Rank	#303	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	0.44
Rank	#267	Overall
	#23	Time Series DBMS

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Website

cambridgesemantics.com/anzograph

www.esgyn.cn

geospock.com

www.ittia.com

Technical documentation

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

www.tiot.jp/riak-docs/riak/kv/latest

Developer

Cambridge Semantics

Esgyn

GeoSpock

ITTIA L.L.C.

OpenSource, formerly Basho Technologies

Initial release

2018

2015

2007

2009

Current release

2.3, January 2021

2.0, September 2019

8.7

3.2.0, December 2022

License

Commercial or Open Source

commercial

free trial version available

commercial

Open Source

Apache version 2, commercial enterprise edition

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++, Java

Java, Javascript

C and C++

Erlang

Server operating systems

Linux

hosted

Linux
Windows

Linux
OS X

Data scheme

Schema-free and OWL/RDFS-schema support

yes

Fixed schema

schema-free

Typing

predefined data types such as float or date

yes

Float/Blob/Integer/String/Unicode/Date/Time/Timestamp/Interval

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

yes

temporal, categorical

yes

restricted

SQL

Support of SQL

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

yes

ANSI SQL for query only (using Presto)

yes

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

JDBC
ODBC
RESTful HTTP API
WebSocket

HTTP API
Native Erlang Interface

Supported programming languages

C++
Java
Python

All languages supporting JDBC/ODBC/ADO.Net

C
C++
JavaScript (Node.js)
Python

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

user defined functions and aggregates

Java Stored Procedures

yes

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

Automatic sharding

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Multi-source replication between multi datacenters

yes

selectable replication factor

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

Eventual Consistency

Foreign keys

Referential integrity

not needed in graphs

yes

links between data sets can be stored

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

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

Access rights for users can be defined per table

Database file passwords

yes, using Riak Security

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More resources

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