DBMS > Atos Standard Common Repository vs. EJDB vs. H2GIS vs. Prometheus vs. TimesTen

System Properties Comparison Atos Standard Common Repository vs. EJDB vs. H2GIS vs. Prometheus vs. TimesTen

Editorial information provided by DB-Engines

Name

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

Description

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

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Spatial extension of H2

Open-source Time Series DBMS and monitoring system

An in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.

Primary database model

Document store
Key-value store

Secondary database models

Relational DBMS

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

Score	0.16
Rank	#324	Overall
	#45	Document stores

Score	0.00
Rank	#386	Overall
	#7	Spatial DBMS

Score	6.92
Rank	#50	Overall
	#3	Time Series DBMS

Score	1.23
Rank	#163	Overall
	#74	Relational DBMS

Website

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

github.com/Softmotions/ejdb

www.h2gis.org

prometheus.io

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

github.com/Softmotions/ejdb/blob/master/README.md

www.h2gis.org/docs/home

prometheus.io/docs

docs.oracle.com/en/database/other-databases/timesten/index.html

Developer

Atos Convergence Creators

Softmotions

CNRS

Oracle

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2016

2012

2013

2015

1998

Current release

1703

Release 22.1

License

Commercial or Open Source

commercial

Open Source

GPLv2

Open Source

LGPL 3.0

Open Source

Apache 2.0

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

Server operating systems

Linux

server-less

Linux
Windows

IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64

Data scheme

Schema and schema-less with LDAP views

schema-free

yes

Typing

predefined data types such as float or date

optional

yes

string, integer, double, bool, date, object_id

yes

Numeric data only

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

Import of XML data possible

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

LDAP

in-process shared library

RESTful HTTP/JSON API

ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC

Supported programming languages

All languages with LDAP bindings

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

Java

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

C
C++
Java
Node.js
PL/SQL
Python

Server-side scripts

Stored procedures

yes

based on H2

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes

based on H2

yes

by Federation

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

none

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

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

yes

based on H2

fine grained access rights according to SQL-standard

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

Introducing the Amazon Timestream for LiveAnalytics Prometheus Connector
8 July 2024, AWS Blog

StarTree eyes observability market with Apache Pinot-based real-time engine
27 September 2024, SiliconANGLE News

How to Monitor an Ubuntu Server With Prometheus: Collecting and Visualizing System Metrics
9 July 2024, Linux Journal

How Cloudflare runs Prometheus at scale
3 March 2023, The Cloudflare Blog

VTEX scales to 150 million metrics using Amazon Managed Service for Prometheus
10 March 2024, AWS Blog

provided by Google News

Share this page