DBMS > Alibaba Cloud AnalyticDB for MySQL vs. GBase vs. HEAVY.AI vs. Oracle Berkeley DB vs. TimesTen

System Properties Comparison Alibaba Cloud AnalyticDB for MySQL vs. GBase vs. HEAVY.AI vs. Oracle Berkeley DB vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

A real-time data warehousing service that can process petabytes of data with high concurrency and low latency. It is fully compatible with the MySQL protocol.

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

Widely used in-process key-value store

An in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.

Primary database model

Relational DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Relational DBMS

Secondary database models

Document store

Spatial DBMS

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

Score	0.92
Rank	#195	Overall
	#91	Relational DBMS

Score	1.11
Rank	#173	Overall
	#78	Relational DBMS

Score	1.41
Rank	#153	Overall
	#71	Relational DBMS

Score	1.88
Rank	#130	Overall
	#23	Key-value stores
	#3	Native XML DBMS

Score	1.26
Rank	#164	Overall
	#75	Relational DBMS

Website

www.alibabacloud.com/product/analyticdb-for-mysql

www.gbase.cn

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

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

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

Technical documentation

www.alibabacloud.com/help/doc-detail/93776.htm

docs.heavy.ai

docs.oracle.com/cd/E17076_05/html/index.html

docs.oracle.com/en/database/other-databases/timesten/index.html

Developer

Alibaba

General Data Technology Co., Ltd.

HEAVY.AI, Inc.

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Oracle

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

Initial release

2004

2016

1994

1998

Current release

GBase 8a, GBase 8s, GBase 8c

5.10, January 2022

18.1.40, May 2020

Release 22.1

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; enterprise edition available

Open Source

commercial license available

commercial

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, Java, Python

C++ and CUDA

C, Java, C++ (depending on the Berkeley DB edition)

Server operating systems

hosted

Linux

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64

Data scheme

yes

schema-free

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

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

yes

Standard with numerous extensions

yes

SQL interfaced based on SQLite is available

yes

APIs and other access methods

JDBC
ODBC

ADO.NET
C API
JDBC
ODBC

JDBC
ODBC
Thrift
Vega

ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC

Supported programming languages

C#
Java
PHP
Python

All languages supporting JDBC/ODBC/Thrift
Python

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

C
C++
Java
Node.js
PL/SQL
Python

Server-side scripts

Stored procedures

yes

user defined functions

PL/SQL

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

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

Implicit feature of the cloud service

yes

Multi-source replication

Source-replica replication

Multi-source replication
Source-replica replication

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

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

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

A real-time data warehousing service that can process PB data with high concurrency...
» more

Competitive advantages

TPC Benchmark: The world leading result in TPC-DS benchmark . TPC-H benchmark for...
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Licensing and pricing models

Available regions: America US Virginia US Silicon Valley Asia China Hong Kong India...
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