DBMS > Amazon Redshift vs. EJDB vs. Hazelcast vs. Kinetica vs. TimesTen

System Properties Comparison Amazon Redshift vs. EJDB vs. Hazelcast vs. Kinetica vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

A widely adopted in-memory data grid

Fully vectorized database across both GPUs and CPUs

In-Memory RDBMS compatible to Oracle

Primary database model

Secondary database models

Document store

JSON support with IMDG 3.12

Spatial DBMS
Time Series DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	0.31
Rank	#296	Overall
	#44	Document stores

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

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

aws.amazon.com/redshift

github.com/Softmotions/ejdb

hazelcast.com

www.kinetica.com

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

docs.aws.amazon.com/redshift

github.com/Softmotions/ejdb/blob/master/README.md

hazelcast.org/imdg/docs

docs.kinetica.com

docs.oracle.com/database/timesten-18.1

Developer

Amazon (based on PostgreSQL)

Softmotions

Hazelcast

Kinetica

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2012

2008

2012

1998

Current release

5.3.6, November 2023

7.1, August 2021

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

Open Source

GPLv2

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

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Implementation language

Java

C, C++

Server operating systems

hosted

server-less

All OS with a Java VM

Linux

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC

in-process shared library

JCache
JPA
Memcached protocol
RESTful HTTP API

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

All languages supporting JDBC/ODBC

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

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

C++
Java
JavaScript (Node.js)
Python

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Event Listeners, Executor Services

user defined functions

PL/SQL

Triggers

yes

Events

yes

triggers when inserted values for one or more columns fall within a specified range

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes

Replicated Map

Source-replica replication

Multi-source replication
Source-replica replication

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 or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

typically not needed, however similar functionality with collection joins possible

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

Read/Write Locking

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

GPU vRAM or System RAM

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Role-based access control

Access rights for users and roles on table level

fine grained access rights according to SQL-standard

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