DBMS > Amazon Redshift vs. Brytlyt vs. Solr vs. Trafodion

System Properties Comparison Amazon Redshift vs. Brytlyt vs. Solr vs. Trafodion

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

Large scale data warehouse service for use with business intelligence tools

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

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

Transactional SQL-on-Hadoop DBMS

Primary database model

Relational DBMS

Search engine

Relational DBMS

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	0.29
Rank	#288	Overall
	#131	Relational DBMS

Score	42.91
Rank	#24	Overall
	#3	Search engines

Website

aws.amazon.com/redshift

brytlyt.io

solr.apache.org

trafodion.apache.org

Technical documentation

docs.aws.amazon.com/redshift

docs.brytlyt.io

solr.apache.org/resources.html

trafodion.apache.org/documentation.html

Developer

Amazon (based on PostgreSQL)

Brytlyt

Apache Software Foundation

Apache Software Foundation, originally developed by HP

Initial release

2012

2016

2006

2014

Current release

5.0, August 2023

9.6.0, April 2024

2.3.0, February 2019

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

Apache 2.0

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

C, C++ and CUDA

Java

C++, Java

Server operating systems

hosted

Linux
OS X
Windows

All OS with a Java VM

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

Linux

Data scheme

yes

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

yes

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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

specific XML-type available, but no XML query functionality.

yes

Secondary indexes

restricted

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

Solr Parallel SQL Interface

yes

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Java API
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

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

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

in PL/pgSQL

Java plugins

Java Stored Procedures

Triggers

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

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

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

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

optimistic locking

ACID

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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.