DBMS > GridDB vs. IBM Db2 Event Store vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Table Storage vs. Quasardb

System Properties Comparison GridDB vs. IBM Db2 Event Store vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Table Storage vs. Quasardb

Editorial information provided by DB-Engines

Name

Description

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

Distributed Event Store optimized for Internet of Things use cases

Globally distributed, horizontally scalable, multi-model database service

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

Distributed, high-performance timeseries database

Primary database model

Time Series DBMS

Event Store
Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Wide column store

Time Series DBMS

Secondary database models

Key-value store
Relational DBMS

Spatial DBMS

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

Score	1.95
Rank	#128	Overall
	#10	Time Series DBMS

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Website

griddb.net

www.ibm.com/products/db2-event-store

azure.microsoft.com/services/cosmos-db

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

quasar.ai

Technical documentation

docs.griddb.net

www.ibm.com/docs/en/db2-event-store

learn.microsoft.com/azure/cosmos-db

doc.quasar.ai/master

Developer

Toshiba Corporation

IBM

Microsoft

quasardb

Initial release

2013

2017

2014

2012

2009

Current release

5.1, August 2022

2.0

3.14.1, January 2024

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 developer edition available

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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++

C and C++

C++

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

hosted

BSD
Linux
OS X
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

yes

JSON types

yes

integer and binary

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

All properties auto-indexed by default

yes

with tags

SQL

Support of SQL

SQL92, SQL-like TQL (Toshiba Query Language)

yes

through the embedded Spark runtime

SQL-like query language

APIs and other access methods

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

RESTful HTTP API

HTTP API

Supported programming languages

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

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

yes

JavaScript

Triggers

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Implicit feature of the cloud service

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Active-active shard replication

yes

Implicit feature of the cloud service

yes

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

Source-replica replication with selectable replication factor

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

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency within container, eventual consistency across containers

Eventual Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID at container level

Multi-item ACID transactions with snapshot isolation within a partition

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

yes

by using LevelDB

In-memory capabilities

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

yes

Transient mode

User concepts

Access control

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

Access rights based on private key authentication or shared access signatures

Cryptographically strong user authentication and audit trail

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.