DBMS > Atos Standard Common Repository vs. GeoSpock vs. HBase vs. SpatiaLite

System Properties Comparison Atos Standard Common Repository vs. GeoSpock vs. HBase vs. SpatiaLite

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Editorial information provided by DB-Engines

Name

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

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

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

Spatial and temporal data processing engine for extreme data scale

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

Spatial extension of SQLite

Primary database model

Document store
Key-value store

Relational DBMS

Wide column store

Spatial DBMS

Secondary database models

Time Series DBMS

Relational DBMS

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

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	1.60
Rank	#149	Overall
	#3	Spatial DBMS

Website

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

geospock.com

hbase.apache.org

www.gaia-gis.it/fossil/libspatialite/index

Technical documentation

hbase.apache.org/book.html

www.gaia-gis.it/gaia-sins/spatialite_topics.html

Developer

Atos Convergence Creators

GeoSpock

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Alessandro Furieri

Initial release

2016

2008

Current release

1703

2.0, September 2019

2.3.4, January 2021

5.0.0, August 2020

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

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

Java

Java, Javascript

Java

C++

Server operating systems

Linux

hosted

Linux
Unix
Windows

using Cygwin

server-less

Data scheme

Schema and schema-less with LDAP views

yes

schema-free, schema definition possible

yes

Typing

predefined data types such as float or date

optional

yes

options to bring your own types, AVRO

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

temporal, categorical

yes

SQL

Support of SQL

ANSI SQL for query only (using Presto)

yes

APIs and other access methods

LDAP

JDBC

Java API
RESTful HTTP API
Thrift

Supported programming languages

All languages with LDAP bindings

C
C#
C++
Groovy
Java
PHP
Python
Scala

Server-side scripts

Stored procedures

yes

Coprocessors in Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Automatic sharding

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Immediate Consistency or Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

Single row ACID (across millions of columns)

ACID

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

LDAP bind authentication

Access rights for users can be defined per table

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

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