DBMS > Drizzle vs. Hypertable vs. Interbase vs. Sequoiadb

System Properties Comparison Drizzle vs. Hypertable vs. Interbase vs. Sequoiadb

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

An open source BigTable implementation based on distributed file systems such as Hadoop

Light-weight proven RDBMS

originally from Borland

NewSQL database with distributed OLTP and SQL

Primary database model

Relational DBMS

Wide column store

Relational DBMS

Document store
Relational DBMS

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

Score	4.08
Rank	#75	Overall
	#41	Relational DBMS

Score	0.50
Rank	#258	Overall
	#41	Document stores
	#120	Relational DBMS

Website

www.embarcadero.com/products/interbase

www.sequoiadb.com

Technical documentation

docs.embarcadero.com/products/interbase

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Drizzle project, originally started by Brian Aker

Hypertable Inc.

Embarcadero

Sequoiadb Ltd.

Initial release

2008

2009

1984

2013

Current release

7.2.4, September 2012

0.9.8.11, March 2016

InterBase 2020, December 2019

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

GNU version 3. Commercial license available

commercial

Open Source

Server: AGPL; Client: Apache V2

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++

Server operating systems

FreeBSD
Linux
OS X

Linux
OS X
Windows

an inofficial Windows port is available

Android
iOS
Linux
OS X
Windows

Linux

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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.

export as XML data possible

Secondary indexes

yes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

SQL-like query language

APIs and other access methods

JDBC

C++ API
Thrift

ADO.NET
JDBC
ODBC

proprietary protocol using JSON

Supported programming languages

C
C++
Java
PHP

C++
Java
Perl
PHP
Python
Ruby

.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

yes

Interbase procedure and trigger language

JavaScript

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

selectable replication factor on file system level

Interbase Change Views

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes

Multiversion concurreny control

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

simple password-based access control

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More resources

DB-Engines blog posts

MySQL won the April ranking; did its forks follow?
1 April 2015, Paul Andlinger

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1 July 2013, Matthias Gelbmann

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