DBMS > Amazon Redshift vs. Derby vs. Hazelcast vs. Teradata Aster vs. TinkerGraph

System Properties Comparison Amazon Redshift vs. Derby vs. Hazelcast vs. Teradata Aster vs. TinkerGraph

Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

Large scale data warehouse service for use with business intelligence tools

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

A widely adopted in-memory data grid

Platform for big data analytics on multistructured data sources and types

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

Primary database model

Secondary database models

Document store

JSON support with IMDG 3.12

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	4.71
Rank	#69	Overall
	#37	Relational DBMS

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	0.08
Rank	#348	Overall
	#35	Graph DBMS

Website

aws.amazon.com/redshift

db.apache.org/derby

hazelcast.com

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

Technical documentation

docs.aws.amazon.com/redshift

db.apache.org/derby/manuals/index.html

hazelcast.org/imdg/docs

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

Hazelcast

Teradata

Initial release

2012

1997

2008

2005

2009

Current release

10.17.1.0, November 2023

5.3.6, November 2023

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Open Source

Apache Version 2; commercial licenses available

commercial

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

Java

Server operating systems

hosted

All OS with a Java VM

Linux

Data scheme

yes

schema-free

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

schema-free

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

yes

in Aster File Store

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC

JDBC

JCache
JPA
Memcached protocol
RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB

TinkerPop 3

Supported programming languages

All languages supporting JDBC/ODBC

Java

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

C
C#
C++
Java
Python
R

Groovy
Java

Server-side scripts

Stored procedures

user defined functions

in Python

Java Stored Procedures

yes

Event Listeners, Executor Services

R packages

Triggers

yes

Events

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

Source-replica replication

yes

Replicated Map

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

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

none

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Relationships in graphs

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

optional

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

fine grained access rights according to SQL-standard

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