DBMS > GBase vs. HEAVY.AI vs. TimesTen vs. WakandaDB

System Properties Comparison GBase vs. HEAVY.AI vs. TimesTen vs. WakandaDB

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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.

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

In-Memory RDBMS compatible to Oracle

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Relational DBMS

Object oriented DBMS

Secondary database models

Spatial DBMS

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

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

www.gbase.cn

github.com/heavyai/heavydb
www.heavy.ai

www.oracle.com/database/technologies/related/timesten.html

wakanda.github.io

Technical documentation

docs.heavy.ai

docs.oracle.com/database/timesten-18.1

wakanda.github.io/doc

Developer

General Data Technology Co., Ltd.

HEAVY.AI, Inc.

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Wakanda SAS

Initial release

2004

2016

1998

2012

Current release

GBase 8a, GBase 8s, GBase 8c

5.10, January 2022

11 Release 2 (11.2.2.8.0)

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; enterprise edition available

commercial

Open Source

AGPLv3, extended commercial license available

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

C++ and CUDA

C++, JavaScript

Server operating systems

Linux

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
OS X
Windows

Data scheme

yes

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

yes

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

JDBC
ODBC
Thrift
Vega

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

C
C++
Java
PL/SQL

JavaScript

Server-side scripts

Stored procedures

user defined functions

PL/SQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

Round robin

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

by means of logfiles and checkpoints

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

fine grained access rights according to SQL-standard

yes

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More resources

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