DBMS > Amazon Redshift vs. BigObject vs. EXASOL vs. Oracle Coherence vs. Solr

System Properties Comparison Amazon Redshift vs. BigObject vs. EXASOL vs. Oracle Coherence vs. Solr

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Analytic DBMS for real-time computations and queries

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Oracles in-memory data grid solution

A widely used distributed, scalable search engine based on Apache Lucene

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Key-value store

Search engine

Secondary database models

Spatial DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	1.92
Rank	#130	Overall
	#22	Key-value stores

Score	42.91
Rank	#24	Overall
	#3	Search engines

Website

aws.amazon.com/redshift

bigobject.io

www.exasol.com

www.oracle.com/java/coherence

solr.apache.org

Technical documentation

docs.aws.amazon.com/redshift

docs.bigobject.io

www.exasol.com/resources

docs.oracle.com/en/middleware/standalone/coherence

solr.apache.org/resources.html

Developer

Amazon (based on PostgreSQL)

BigObject, Inc.

Exasol

Oracle

Apache Software Foundation

Initial release

2012

2015

2000

2007

2006

Current release

14.1, August 2023

9.6.0, April 2024

License

Commercial or Open Source

commercial

free community edition available

commercial

Open Source

Apache Version 2

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

Java

Server operating systems

hosted

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Data scheme

yes

schema-free

yes

Dynamic Fields enables on-the-fly addition of new fields

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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

restricted

yes

All search fields are automatically indexed

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like DML and DDL statements

yes

Solr Parallel SQL Interface

APIs and other access methods

JDBC
ODBC

fluentd
ODBC
RESTful HTTP API

.Net
JDBC
ODBC
WebSocket

JCache
JPA
RESTful HTTP API

Java API
RESTful HTTP/JSON API

Supported programming languages

All languages supporting JDBC/ODBC

Java
Lua
Python
R

.Net
C++
Java

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

user defined functions

in Python

Lua

user defined functions

Java plugins

Triggers

yes

Live Events

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes, with selectable consistency level

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

configurable

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

yes

optionally

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

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

authentification to access the cache via certificates or http basic authentication

yes

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