DBMS > Atos Standard Common Repository vs. etcd vs. Lovefield vs. PlanetScale vs. SiteWhere

System Properties Comparison Atos Standard Common Repository vs. etcd vs. Lovefield vs. PlanetScale vs. SiteWhere

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

Embeddable relational database for web apps written in pure JavaScript

Scalable, distributed, serverless MySQL database platform built on top of Vitess

M2M integration platform for persisting/querying time series data

Primary database model

Document store
Key-value store

Key-value store

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	7.25
Rank	#54	Overall
	#5	Key-value stores

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	1.59
Rank	#151	Overall
	#70	Relational DBMS

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Website

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

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

google.github.io/lovefield

planetscale.com

github.com/sitewhere/sitewhere

Technical documentation

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

github.com/google/lovefield/blob/master/docs/spec_index.md

planetscale.com/docs

sitewhere1.sitewhere.io/index.html

Developer

Atos Convergence Creators

Google

PlanetScale

SiteWhere

Initial release

2016

2014

2020

2010

Current release

1703

3.4, August 2019

2.1.12, February 2017

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

Open Source

Common Public Attribution License Version 1.0

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

JavaScript

Java

Server operating systems

Linux

FreeBSD
Linux
Windows

experimental

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Docker
Linux
macOS

Linux
OS X
Windows

Data scheme

Schema and schema-less with LDAP views

schema-free

yes

predefined scheme

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 query language

via JavaScript builder pattern

yes

with proprietary extensions

APIs and other access methods

LDAP

gRPC
JSON over HTTP

ADO.NET
JDBC
MySQL protocol
ODBC

HTTP REST

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

JavaScript

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

proprietary syntax

Triggers

yes

yes, watching key changes

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

Sharding

based on HBase

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.

none

Multi-source replication
Source-replica replication

selectable replication factor

based on HBase

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

Eventual Consistency across shards
Immediate Consistency within a shard

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

Atomic execution of specific operations

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

yes

User concepts

Access control

LDAP bind authentication

Users with fine-grained authorization concept

no user groups or roles

Users with fine-grained authorization concept

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