DBMS > GBase vs. GridGain vs. SiteWhere vs. Warp 10

System Properties Comparison GBase vs. GridGain vs. SiteWhere vs. Warp 10

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Editorial information provided by DB-Engines

Name

Description

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

GridGain is an in-memory computing platform, built on Apache Ignite

M2M integration platform for persisting/querying time series data

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Relational DBMS

Columnar
Key-value store
Object oriented DBMS
Relational DBMS

Time Series DBMS

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

Score	1.11
Rank	#173	Overall
	#78	Relational DBMS

Score	1.48
Rank	#150	Overall
	#1	Columnar
	#26	Key-value stores
	#2	Object oriented DBMS
	#69	Relational DBMS

Score	0.07
Rank	#347	Overall
	#33	Time Series DBMS

Score	0.06
Rank	#351	Overall
	#35	Time Series DBMS

Website

www.gbase.cn

www.gridgain.com

github.com/sitewhere/sitewhere

www.warp10.io

Technical documentation

www.gridgain.com/docs/index.html

sitewhere1.sitewhere.io/index.html

www.warp10.io/content/02_Getting_started

Developer

General Data Technology Co., Ltd.

GridGain Systems, Inc.

SiteWhere

SenX

Initial release

2004

2007

2010

2015

Current release

GBase 8a, GBase 8s, GBase 8c

GridGain 8.5.1

License

Commercial or Open Source

commercial

commercial, open source

Open Source

Common Public Attribution License Version 1.0

Open Source

Apache License 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, Java, Python

Java, C++, .Net, Python, REST, SQL

Java

Server operating systems

Linux

Linux
OS X
Solaris
Windows
z/OS

Linux
OS X
Windows

Data scheme

yes

predefined scheme

schema-free

Typing

predefined data types such as float or date

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.

yes

Secondary indexes

yes

SQL

Support of SQL

Standard with numerous extensions

ANSI-99 for query and DML statements, subset of DDL

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

HTTP REST

HTTP API
Jupyter
WebSocket

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

user defined functions

yes (compute grid and cache interceptors can be used instead)

yes

WarpScript

Triggers

yes

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

based on HBase

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes (replicated cache)

selectable replication factor

based on HBase

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

yes

Role-based access control
Security Hooks for custom implementations

Users with fine-grained authorization concept

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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