DBMS > Atos Standard Common Repository vs. etcd vs. GeoMesa vs. Hive

System Properties Comparison Atos Standard Common Repository vs. etcd vs. GeoMesa vs. Hive

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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.

Description

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

A distributed reliable key-value store

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Primary database model

Document store
Key-value store

Key-value store

Spatial DBMS

Relational DBMS

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

Score	7.64
Rank	#54	Overall
	#5	Key-value stores

Score	0.81
Rank	#214	Overall
	#4	Spatial DBMS

Score	62.59
Rank	#18	Overall
	#12	Relational DBMS

Website

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

etcd.io
github.com/etcd-io/etcd

www.geomesa.org

hive.apache.org

Technical documentation

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

www.geomesa.org/documentation/stable/user/index.html

cwiki.apache.org/confluence/display/Hive/Home

Developer

Atos Convergence Creators

CCRi and others

Apache Software Foundation

initially developed by Facebook

Initial release

2016

2014

2012

Current release

1703

3.4, August 2019

4.0.5, February 2024

3.1.3, April 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache License 2.0

Open Source

Apache Version 2

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

Scala

Java

Server operating systems

Linux

FreeBSD
Linux
Windows

experimental

All OS with a Java VM

Data scheme

Schema and schema-less with LDAP views

schema-free

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

SQL-like DML and DDL statements

APIs and other access methods

LDAP

gRPC
JSON over HTTP

JDBC
ODBC
Thrift

Supported programming languages

All languages with LDAP bindings

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

C++
Java
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Triggers

yes

yes, watching key changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

depending on storage layer

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

depending on storage layer

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

depending on storage layer

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

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

depending on storage layer

User concepts

Access control

LDAP bind authentication

yes

depending on the DBMS used for storage

Access rights for users, groups and roles

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