DBMS > GridDB vs. TDSQL for MySQL vs. VoltDB vs. YottaDB

System Properties Comparison GridDB vs. TDSQL for MySQL vs. VoltDB vs. YottaDB

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Editorial information provided by DB-Engines

Name

Description

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

A high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

A fast and solid embedded Key-value store

Primary database model

Time Series DBMS

Relational DBMS

Key-value store

Secondary database models

Key-value store
Relational DBMS

Document store
Spatial DBMS

Relational DBMS

using the Octo plugin

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

Score	1.95
Rank	#128	Overall
	#10	Time Series DBMS

Score	0.85
Rank	#205	Overall
	#95	Relational DBMS

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Score	0.20
Rank	#317	Overall
	#47	Key-value stores

Website

griddb.net

www.tencentcloud.com/products/dcdb

www.voltdb.com

yottadb.com

Technical documentation

docs.griddb.net

www.tencentcloud.com/document/product/1042

docs.voltdb.com

yottadb.com/resources/documentation

Developer

Toshiba Corporation

Tencent

VoltDB Inc.

YottaDB, LLC

Initial release

2013

2010

2001

Current release

5.1, August 2022

11.3, April 2022

License

Commercial or Open Source

Open Source

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

commercial

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

Open Source

AGPL 3.0

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

C++

Java, C++

Server operating systems

Linux

hosted

Linux
OS X

for development

Docker
Linux

Data scheme

yes

schema-free

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

SQL

Support of SQL

SQL92, SQL-like TQL (Toshiba Query Language)

yes

only a subset of SQL 99

by using the Octo plugin

APIs and other access methods

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

JDBC
ODBC

Java API
JDBC
RESTful HTTP/JSON API

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

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

C
C#
C++
Java
PHP
Python
Ruby

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic sharding

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

yes

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

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency within container, eventual consistency across containers

Immediate Consistency

Foreign keys

Referential integrity

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID at container level

ACID

Transactions are executed single-threaded within stored procedures

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

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

Access rights for users can be defined per database

Users with fine-grained authorization concept

Users and roles with access to stored procedures

Users and groups based on OS-security mechanisms

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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More resources

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provided by Google News

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