DBMS > Amazon Redshift vs. Apache Druid vs. Apache Pinot vs. GigaSpaces vs. SAP SQL Anywhere

System Properties Comparison Amazon Redshift vs. Apache Druid vs. Apache Pinot vs. GigaSpaces vs. SAP SQL Anywhere

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Primary database model

Relational DBMS

Relational DBMS
Time Series DBMS

Relational DBMS

Document store
Object oriented DBMS

Values are user defined objects

Relational DBMS

Secondary database models

Graph DBMS
Search engine

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	0.38
Rank	#275	Overall
	#126	Relational DBMS

Score	1.03
Rank	#188	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Website

aws.amazon.com/redshift

druid.apache.org

pinot.apache.org

www.gigaspaces.com

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

docs.aws.amazon.com/redshift

druid.apache.org/docs/latest/design

docs.pinot.apache.org

docs.gigaspaces.com/latest/landing.html

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation and contributors

Gigaspaces Technologies

SAP

formerly Sybase

Initial release

2012

2015

2000

1992

Current release

29.0.1, April 2024

1.0.0, September 2023

15.5, September 2020

17, July 2015

License

Commercial or Open Source

commercial

Open Source

Apache license v2

Open Source

Apache Version 2.0

Open Source

Apache Version 2; Commercial licenses 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

Java

Java, C++, .Net

Server operating systems

hosted

Linux
OS X
Unix

All OS with a Java JDK11 or higher

Linux
macOS
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

yes

schema-less columns are supported

yes

schema-free

yes

Typing

predefined data types such as float or date

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.

XML can be used for describing objects metadata

yes

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL for querying

SQL-like query language

SQL-99 for query and DML statements

yes

APIs and other access methods

JDBC
ODBC

JDBC
RESTful HTTP/JSON API

JDBC

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Go
Java
Python

.Net
C++
Java
Python
Scala

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

yes

yes, in C/C++, Java, .Net or Perl

Triggers

yes, event driven architecture

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, via HDFS, S3 or other storage engines

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

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

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Role-based access control

fine grained access rights according to SQL-standard

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