DBMS > atoti vs. Drizzle vs. JaguarDB vs. Teradata

System Properties Comparison atoti vs. Drizzle vs. JaguarDB vs. Teradata

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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

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

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

Performant, highly scalable DBMS for AI and IoT applications

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Object oriented DBMS

Relational DBMS

Key-value store
Vector DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.61
Rank	#243	Overall
	#11	Object oriented DBMS

Score	0.06
Rank	#381	Overall
	#59	Key-value stores
	#15	Vector DBMS

Score	44.87
Rank	#22	Overall
	#15	Relational DBMS

Website

atoti.io

www.jaguardb.com

www.teradata.com

Technical documentation

docs.atoti.io

www.jaguardb.com/support.html

docs.teradata.com

Developer

ActiveViam

Drizzle project, originally started by Brian Aker

DataJaguar, Inc.

Teradata

Initial release

2008

2015

1984

Current release

7.2.4, September 2012

3.3 July 2023

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

commercial

free versions available

Open Source

GNU GPL

Open Source

GPL V3.0

commercial

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

Java

C++

the server part. Clients available in other languages

Server operating systems

FreeBSD
Linux
OS X

Linux

hosted
Linux

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

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

Multidimensional Expressions (MDX)

yes

with proprietary extensions

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

SQL 2016 + extensions

APIs and other access methods

JDBC

JDBC
ODBC

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

C
C++
Java
PHP

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

Python

yes

UDFs, stored procedures, table functions in parallel

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source 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

Eventual Consistency

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, multi-version concurrency control (MVCC)

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

rights management via user accounts

fine grained access rights according to SQL-standard

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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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Teradata is the most popular data warehouse DBMS
2 April 2013, Paul Andlinger

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Recent citations in the news

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