DBMS > Amazon Redshift vs. Drizzle vs. Elasticsearch vs. Fujitsu Enterprise Postgres vs. Rockset

System Properties Comparison Amazon Redshift vs. Drizzle vs. Elasticsearch vs. Fujitsu Enterprise Postgres vs. Rockset

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

Large scale data warehouse service for use with business intelligence tools

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

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Primary database model

Secondary database models

Document store
Spatial DBMS
Vector DBMS

Document store
Spatial DBMS

Relational DBMS
Search engine

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	135.35
Rank	#7	Overall
	#1	Search engines

Score	0.31
Rank	#285	Overall
	#129	Relational DBMS

Score	0.79
Rank	#211	Overall
	#35	Document stores

Website

aws.amazon.com/redshift

www.elastic.co/elasticsearch

www.postgresql.fastware.com

rockset.com

Technical documentation

docs.aws.amazon.com/redshift

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

www.postgresql.fastware.com/product-manuals

docs.rockset.com

Developer

Amazon (based on PostgreSQL)

Drizzle project, originally started by Brian Aker

Elastic

PostgreSQL Global Development Group, Fujitsu Australia Software Technology

Rockset

Initial release

2012

2008

2010

2019

Current release

7.2.4, September 2012

8.6, January 2023

Fujitsu Enterprise Postgres 14, January 2022

License

Commercial or Open Source

commercial

Open Source

GNU GPL

Open Source

Elastic License

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

C++

Java

C++

Server operating systems

hosted

FreeBSD
Linux
OS X

All OS with a Java VM

Linux
Windows

hosted

Data scheme

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

yes

schema-free

Typing

predefined data types such as float or date

yes

dynamic 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.

ingestion from XML files supported

Secondary indexes

restricted

yes

All search fields are automatically indexed

yes

all fields are automatically indexed

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

with proprietary extensions

SQL-like query language

yes

Read-only SQL queries, including JOINs

APIs and other access methods

JDBC
ODBC

JDBC

Java API
RESTful HTTP/JSON API

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

HTTP REST

Supported programming languages

All languages supporting JDBC/ODBC

C
C++
Java
PHP

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

in Python

yes

user defined functions

Triggers

hooks for callbacks inside the server can be used.

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

partitioning by range, list and by hash

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

yes

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Immediate Consistency

Eventual 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

Concurrency

Support for concurrent manipulation of data

yes

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

Memcached and Redis integration

User concepts

Access control

fine grained access rights according to SQL-standard

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

Access rights for users and organizations can be defined via Rockset console

More information provided by the system vendor

Specific characteristics

100% compatible with community PostgreSQL
» more

Competitive advantages

Built-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
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Typical application scenarios

Transactional payments applications, reporting and mixed workloads.
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Market metrics

Over 30 years experience in database technology. Over 20 years in Postgres development...
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Licensing and pricing models

Core based licensing
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