DBMS > Apache Doris vs. GridDB vs. Microsoft Azure Table Storage vs. Riak TS vs. Transbase

System Properties Comparison Apache Doris vs. GridDB vs. Microsoft Azure Table Storage vs. Riak TS vs. Transbase

Editorial information provided by DB-Engines

Name

Description

An MPP-based analytics DBMS embracing the MySQL protocol

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

A Wide Column Store for rapid development using massive semi-structured datasets

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

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Secondary database models

Key-value store
Relational DBMS

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

Score	0.60
Rank	#247	Overall
	#113	Relational DBMS

Score	2.09
Rank	#120	Overall
	#10	Time Series DBMS

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Website

doris.apache.org
github.com/apache/doris

griddb.net

azure.microsoft.com/en-us/services/storage/tables

www.transaction.de/en/products/transbase.html

Technical documentation

github.com/apache/doris/wiki

docs.griddb.net

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

www.transaction.de/en/products/transbase/features.html

Developer

Apache Software Foundation, originally contributed from Baidu

Toshiba Corporation

Microsoft

Open Source, formerly Basho Technologies

Transaction Software GmbH

Initial release

2017

2013

2012

2015

1987

Current release

1.2.2, February 2023

5.1, August 2022

3.0.0, September 2022

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

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

commercial

Open Source

commercial

free development license

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Erlang

C and C++

Server operating systems

Linux

hosted

Linux
OS X

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

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.

Secondary indexes

yes

restricted

yes

SQL

Support of SQL

yes

SQL92, SQL-like TQL (Toshiba Query Language)

yes, limited

yes

APIs and other access methods

JDBC
MySQL client

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

RESTful HTTP API

HTTP API
Native Erlang Interface

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Java

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

.Net
C#
C++
Java
JavaScript (Node.js)
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
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

user defined functions

Erlang

yes

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

selectable replication factor

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Immediate Consistency

Immediate consistency within container, eventual consistency across containers

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between datasets can be stored

yes

Transaction concepts

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

ACID at container level

optimistic locking

yes

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

fine grained access rights according to SQL-standard

Access rights for users can be defined per database

Access rights based on private key authentication or shared access signatures

fine grained access rights according to SQL-standard

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

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

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