DBMS > GBase vs. GeoMesa vs. Tkrzw vs. Transwarp Hippo

System Properties Comparison GBase vs. GeoMesa vs. Tkrzw 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.

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

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

Primary database model

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

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Score	0.00
Rank	#383	Overall
	#13	Vector DBMS

Website

www.gbase.cn

www.geomesa.org

dbmx.net/tkrzw

www.transwarp.cn/en/subproduct/hippo

Technical documentation

www.geomesa.org/documentation/stable/user/index.html

Developer

General Data Technology Co., Ltd.

CCRi and others

Mikio Hirabayashi

Initial release

2004

2014

2020

2023

Current release

GBase 8a, GBase 8s, GBase 8c

4.0.5, February 2024

0.9.3, August 2020

1.0, May 2023

License

Commercial or Open Source

commercial

Open Source

Apache License 2.0

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, Java, Python

Scala

C++

Server operating systems

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

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

RESTful HTTP API

Supported programming languages

C++
Java
Python
Ruby

C++
Java
Python

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

depending on storage layer

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on storage layer

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

depending on storage layer

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.

depending on storage layer

yes

using specific database classes

yes

User concepts

Access control

yes

depending on the DBMS used for storage

Role based access control and fine grained access rights

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