DBMS > Atos Standard Common Repository vs. etcd vs. NSDb vs. SiteWhere vs. Spark SQL

System Properties Comparison Atos Standard Common Repository vs. etcd vs. NSDb vs. SiteWhere vs. Spark SQL

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

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

M2M integration platform for persisting/querying time series data

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Document store
Key-value store

Key-value store

Time Series DBMS

Relational DBMS

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

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

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Website

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

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

nsdb.io

github.com/sitewhere/sitewhere

spark.apache.org/sql

Technical documentation

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

nsdb.io/Architecture

sitewhere1.sitewhere.io/index.html

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Atos Convergence Creators

SiteWhere

Apache Software Foundation

Initial release

2016

2017

2010

2014

Current release

1703

3.4, August 2019

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

Open Source

Common Public Attribution License Version 1.0

Open Source

Apache 2.0

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

Java, Scala

Java

Scala

Server operating systems

Linux

FreeBSD
Linux
Windows

experimental

Linux
macOS

Linux
OS X
Windows

Data scheme

Schema and schema-less with LDAP views

schema-free

predefined scheme

yes

Typing

predefined data types such as float or date

optional

yes: int, bigint, decimal, string

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

all fields are automatically indexed

SQL

Support of SQL

SQL-like query language

SQL-like DML and DDL statements

APIs and other access methods

LDAP

gRPC
JSON over HTTP

gRPC
HTTP REST
WebSocket

HTTP REST

JDBC
ODBC

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

Java
Scala

Java
Python
R
Scala

Server-side scripts

Stored procedures

Triggers

yes

yes, watching key changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

based on HBase

yes, utilizing Spark Core

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.

selectable replication factor

based on HBase

none

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

Immediate 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

Using Apache Lucene

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

Users with fine-grained authorization concept

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