DBMS > Drizzle vs. OpenTSDB vs. SAP Adaptive Server vs. Sequoiadb

System Properties Comparison Drizzle vs. OpenTSDB vs. SAP Adaptive Server 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.

Description

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

Scalable Time Series DBMS based on HBase

The SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMS

NewSQL database with distributed OLTP and SQL

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Document store
Relational DBMS

Secondary database models

Spatial DBMS

with Boeing's Spatial Query Server

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

Score	1.59
Rank	#140	Overall
	#12	Time Series DBMS

Score	32.67
Rank	#25	Overall
	#17	Relational DBMS

Score	0.42
Rank	#263	Overall
	#41	Document stores
	#121	Relational DBMS

Website

opentsdb.net

www.sap.com/products/technology-platform/sybase-ase.html

www.sequoiadb.com

Technical documentation

opentsdb.net/docs/build/html/index.html

help.sap.com/docs/SAP_ASE

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

Developer

Drizzle project, originally started by Brian Aker

currently maintained by Yahoo and other contributors

SAP, Sybase

Sequoiadb Ltd.

Initial release

2008

2011

1987

2013

Current release

7.2.4, September 2012

16.0

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

LGPL

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++

Java

C and C++

C++

Server operating systems

FreeBSD
Linux
OS X

Linux
Windows

AIX
HP-UX
Linux
Solaris
Unix
Windows

Linux

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

numeric data for metrics, strings for tags

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.

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

SQL-like query language

APIs and other access methods

JDBC

HTTP API
Telnet API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

proprietary protocol using JSON

Supported programming languages

C
C++
Java
PHP

Erlang
Go
Java
Python
R
Ruby

C
C++
Cobol
Java
Java
Perl
PHP
Python

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

Java and Transact-SQL

JavaScript

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on HBase

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

selectable replication factor

based on HBase

Multi-source replication
Source-replica 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

based on HBase

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

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.

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

Has MySQL finally lost its mojo?
1 July 2013, Matthias Gelbmann

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Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

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