DBMS > Atos Standard Common Repository vs. EsgynDB vs. GreptimeDB vs. PostGIS vs. Transwarp ArgoDB

System Properties Comparison Atos Standard Common Repository vs. EsgynDB vs. GreptimeDB vs. PostGIS vs. Transwarp ArgoDB

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

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

An open source Time Series DBMS built for increased scalability, high performance and efficiency

Spatial extension of PostgreSQL

Distributed Analytical Database to replace Hadoop+MPP hybrid architecture

Primary database model

Document store
Key-value store

Secondary database models

Relational DBMS

Search engine

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

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	0.12
Rank	#351	Overall
	#34	Time Series DBMS

Score	21.72
Rank	#29	Overall
	#1	Spatial DBMS

Score	0.12
Rank	#348	Overall
	#151	Relational DBMS

Website

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

www.esgyn.cn

greptime.com

postgis.net

www.transwarp.cn/en/product/argodb

Technical documentation

docs.greptime.com

postgis.net/documentation

docs.transwarp.cn/#/documents-support/docs?category=ARGODB

Developer

Atos Convergence Creators

Esgyn

Greptime Inc.

Transwarp

Initial release

2016

2015

2022

2005

Current release

1703

3.4.2, February 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

GPL v2.0

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

C++, Java

Rust

Server operating systems

Linux

Android
Docker
FreeBSD
Linux
macOS
Windows

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

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

yes

APIs and other access methods

LDAP

ADO.NET
JDBC
ODBC

gRPC
HTTP API
JDBC

Supported programming languages

All languages with LDAP bindings

All languages supporting JDBC/ODBC/ADO.Net

C++
Erlang
Go
Java
JavaScript

Server-side scripts

Stored procedures

Java Stored Procedures

Python

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

yes

based on PostgreSQL

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication between multi datacenters

yes

based on PostgreSQL

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

Foreign keys

Referential integrity

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

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

fine grained access rights according to SQL-standard

Simple rights management via user accounts

yes

based on PostgreSQL

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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