DBMS > Drizzle vs. InfluxDB vs. Oracle Rdb vs. SQLite vs. Teradata Aster

System Properties Comparison Drizzle vs. InfluxDB vs. Oracle Rdb vs. SQLite vs. Teradata Aster

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.

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

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

DBMS for storing time series, events and metrics

Widely used embeddable, in-process RDBMS

Platform for big data analytics on multistructured data sources and types

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

with GEO package

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

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	1.08
Rank	#184	Overall
	#85	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

www.influxdata.com/products/influxdb-overview

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

www.sqlite.org

Technical documentation

docs.influxdata.com/influxdb

www.oracle.com/database/technologies/related/rdb-doc.html

www.sqlite.org/docs.html

Developer

Drizzle project, originally started by Brian Aker

Oracle, originally developed by Digital Equipment Corporation (DEC)

Dwayne Richard Hipp

Teradata

Initial release

2008

2013

1984

2000

2005

Current release

7.2.4, September 2012

2.7.6, April 2024

7.4.1.1, 2021

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

MIT-License; commercial enterprise version available

commercial

Open Source

Public Domain

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

C++

Server operating systems

FreeBSD
Linux
OS X

Linux
OS X

through Homebrew

HP Open VMS

server-less

Linux

Data scheme

yes

schema-free

Flexible Schema (defined schema, partial schema, schema free)

yes

dynamic column types

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

Typing

predefined data types such as float or date

yes

Numeric data and Strings

yes

not rigid because of 'dynamic typing' concept.

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

in Aster File Store

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

SQL-like query language

yes

SQL-92 is not fully supported

yes

APIs and other access methods

JDBC

HTTP API
JSON over UDP

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

C
C++
Java
PHP

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

R packages

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

in enterprise version only

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

selectable replication factor

in enterprise version only

none

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

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

yes, on a single node

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

Depending on used storage engine

yes

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

simple rights management via user accounts

fine grained access rights according to SQL-standard

More information provided by the system vendor

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