DBMS > Apache Drill vs. Atos Standard Common Repository vs. GridDB vs. Riak TS vs. SWC-DB

System Properties Comparison Apache Drill vs. Atos Standard Common Repository vs. GridDB vs. Riak TS vs. SWC-DB

Editorial information provided by DB-Engines

Name

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

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

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

Scalable in-memory time series database optimized for IoT and Big Data

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

A high performance, scalable Wide Column DBMS

Primary database model

Document store
Relational DBMS

Document store
Key-value store

Time Series DBMS

Wide column store

Secondary database models

Key-value store
Relational DBMS

Time Series DBMS

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

Score	1.95
Rank	#127	Overall
	#23	Document stores
	#60	Relational DBMS

Score	1.95
Rank	#128	Overall
	#10	Time Series DBMS

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

drill.apache.org

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

griddb.net

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

drill.apache.org/docs

docs.griddb.net

www.tiot.jp/riak-docs/riak/ts/latest

Developer

Apache Software Foundation

Atos Convergence Creators

Toshiba Corporation

Open Source, formerly Basho Technologies

Alex Kashirin

Initial release

2012

2016

2013

2015

2020

Current release

1.20.3, January 2023

1703

5.1, August 2022

3.0.0, September 2022

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Erlang

C++

Server operating systems

Linux
OS X
Windows

Linux

Linux
OS X

Linux

Data scheme

schema-free

Schema and schema-less with LDAP views

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

yes

numerical, string, blob, geometry, boolean, timestamp

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

restricted

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

SQL92, SQL-like TQL (Toshiba Query Language)

yes, limited

SQL-like query language

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

LDAP

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

HTTP API
Native Erlang Interface

Proprietary protocol
Thrift

Supported programming languages

C++

All languages with LDAP bindings

C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

C++

Server-side scripts

Stored procedures

user defined functions

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency or Eventual Consistency depending on configuration

Immediate consistency within container, eventual consistency across containers

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between datasets can be stored

Transaction concepts

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

Atomic execution of specific operations

ACID at container level

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

In-memory capabilities

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

Depending on the underlying data source

yes

User concepts

Access control

Depending on the underlying data source

LDAP bind authentication

Access rights for users can be defined per database

More information provided by the system vendor

Specific characteristics

GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more

Competitive advantages

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more

Typical application scenarios

Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more

Key customers

Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more

Market metrics

GitHub trending repository
» more

Licensing and pricing models

Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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

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