DBMS > Amazon Redshift vs. Hazelcast vs. ObjectBox vs. SAP HANA vs. Sphinx

System Properties Comparison Amazon Redshift vs. Hazelcast vs. ObjectBox vs. SAP HANA vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

A widely adopted in-memory data grid

Extremely fast embedded database for small devices, IoT and Mobile

In-memory, column based data store. Available as appliance or cloud service

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Secondary database models

Document store

JSON support with IMDG 3.12

Time Series DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	5.46
Rank	#61	Overall
	#7	Key-value stores

Score	1.29
Rank	#166	Overall
	#5	Object oriented DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	5.95
Rank	#55	Overall
	#5	Search engines

Website

aws.amazon.com/redshift

hazelcast.com

objectbox.io

www.sap.com/products/hana.html

sphinxsearch.com

Technical documentation

docs.aws.amazon.com/redshift

hazelcast.org/imdg/docs

docs.objectbox.io

help.sap.com/hana

sphinxsearch.com/docs

Developer

Amazon (based on PostgreSQL)

Hazelcast

ObjectBox Limited

SAP

Sphinx Technologies Inc.

Initial release

2012

2008

2017

2010

2001

Current release

5.3.6, November 2023

2.0 SPS07 (April 4, 2023), April 2023

3.5.1, February 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache License 2.0

commercial

Open Source

GPL version 2, commercial licence available

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C and C++

C++

Server operating systems

hosted

All OS with a Java VM

Android
iOS
Linux
macOS
Windows

Appliance or cloud-service

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

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.

yes

the object must implement a serialization strategy

Secondary indexes

restricted

yes

full-text index on all search fields

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language

yes

SQL-like query language (SphinxQL)

APIs and other access methods

JDBC
ODBC

JCache
JPA
Memcached protocol
RESTful HTTP API

Proprietary native API

JDBC
ODBC

Proprietary protocol

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Event Listeners, Executor Services

SQLScript, R

Triggers

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

online/offline synchronization between client and server

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

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

one or two-phase-commit; repeatable reads; read commited

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Sphinx index.

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

Role-based access control

yes

More information provided by the system vendor

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