DBMS > Amazon Redshift vs. Graphite vs. Oracle vs. RavenDB vs. Teradata Aster

System Properties Comparison Amazon Redshift vs. Graphite vs. Oracle vs. RavenDB vs. Teradata Aster

Editorial information provided by DB-Engines

Name

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

Description

Large scale data warehouse service for use with business intelligence tools

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Widely used RDBMS

Open Source Operational and Transactional Enterprise NoSQL Document Database

Platform for big data analytics on multistructured data sources and types

Primary database model

Secondary database models

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	4.57
Rank	#73	Overall
	#5	Time Series DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	2.92
Rank	#101	Overall
	#18	Document stores

Website

aws.amazon.com/redshift

github.com/graphite-project/graphite-web

www.oracle.com/database

ravendb.net

Technical documentation

docs.aws.amazon.com/redshift

graphite.readthedocs.io

docs.oracle.com/en/database

ravendb.net/docs

Developer

Amazon (based on PostgreSQL)

Chris Davis

Oracle

Hibernating Rhinos

Teradata

Initial release

2012

2006

1980

2010

2005

Current release

23c, September 2023

5.4, July 2022

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

restricted free version is available

Open Source

AGPL version 3, 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

Python

C and C++

Server operating systems

hosted

Linux
Unix

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Linux
macOS
Raspberry Pi
Windows

Linux

Data scheme

yes

Schemaless in JSON and XML columns

schema-free

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 only

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

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

with proprietary extensions

SQL-like query language (RQL)

yes

APIs and other access methods

JDBC
ODBC

HTTP API
Sockets

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

All languages supporting JDBC/ODBC

JavaScript (Node.js)
Python

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

user defined functions

in Python

PL/SQL

also stored procedures in Java possible

yes

R packages

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Multi-source replication
Source-replica replication

Multi-source replication

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

can be realized in PL/SQL

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

isolation level can be parameterized

ACID, Cluster-wide transaction available

ACID

Concurrency

Support for concurrent manipulation of data

yes

locking

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

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

fine grained access rights according to SQL-standard

Authorization levels configured per client per database

fine grained access rights according to SQL-standard

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