DBMS > GridDB vs. IBM Db2 warehouse vs. Machbase Neo vs. Sequoiadb

System Properties Comparison GridDB vs. IBM Db2 warehouse vs. Machbase Neo vs. Sequoiadb

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Editorial information provided by DB-Engines

Name

Description

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

Cloud-based data warehousing service

TimeSeries DBMS for AIoT and BigData

NewSQL database with distributed OLTP and SQL

Primary database model

Time Series DBMS

Relational DBMS

Time Series DBMS

Document store
Relational DBMS

Secondary database models

Key-value store
Relational DBMS

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

Score	1.91
Rank	#123	Overall
	#10	Time Series DBMS

Score	1.26
Rank	#162	Overall
	#73	Relational DBMS

Score	0.07
Rank	#348	Overall
	#34	Time Series DBMS

Score	0.42
Rank	#263	Overall
	#41	Document stores
	#121	Relational DBMS

Website

griddb.net

www.ibm.com/products/db2/warehouse

machbase.com

www.sequoiadb.com

Technical documentation

docs.griddb.net

machbase.com/dbms

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Toshiba Corporation

IBM

Machbase

Sequoiadb Ltd.

Initial release

2013

2014

2013

Current release

5.1, August 2022

V8.0, August 2023

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

free test version available

Open Source

Server: AGPL; Client: Apache V2

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++

Server operating systems

Linux

hosted

Linux
macOS
Windows

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

yes

oid, date, timestamp, binary, regex

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.

Import/export of XML data possible

Secondary indexes

yes

SQL

Support of SQL

SQL92, SQL-like TQL (Toshiba Query Language)

yes

SQL-like query language

APIs and other access methods

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

.NET Client API
JDBC
ODBC
OLE DB

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

proprietary protocol using JSON

Supported programming languages

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

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

PL/SQL, SQL PL

JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

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

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency within container, eventual consistency across containers

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID at container level

ACID

Document is locked during a transaction

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

volatile and lookup table

User concepts

Access control

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

simple password-based access control

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