DBMS > GBase vs. GridGain vs. SWC-DB vs. Transwarp Hippo

System Properties Comparison GBase vs. GridGain vs. SWC-DB vs. Transwarp Hippo

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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

A high performance, scalable Wide Column DBMS

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Wide column store

Vector DBMS

Secondary database models

Time Series DBMS

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

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Score	0.00
Rank	#383	Overall
	#13	Vector DBMS

Website

www.gbase.cn

www.gridgain.com

github.com/kashirin-alex/swc-db
www.swcdb.org

www.transwarp.cn/en/subproduct/hippo

Technical documentation

www.gridgain.com/docs/index.html

Developer

General Data Technology Co., Ltd.

GridGain Systems, Inc.

Alex Kashirin

Initial release

2004

2007

2020

2023

Current release

GBase 8a, GBase 8s, GBase 8c

GridGain 8.5.1

0.5, April 2021

1.0, May 2023

License

Commercial or Open Source

commercial

Open Source

GPL V3

commercial

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

C++

Server operating systems

Linux

Linux
OS X
Solaris
Windows

Linux

Linux
macOS

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

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

SQL-like query language

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

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

Proprietary protocol
Thrift

RESTful HTTP API

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

C++

C++
Java
Python

Server-side scripts

Stored procedures

user defined functions

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

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes (replicated cache)

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

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

Security Hooks for custom implementations

Role based access control and fine grained access rights

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