DBMS > Amazon Redshift vs. Rockset vs. Teradata Aster vs. XTDB

System Properties Comparison Amazon Redshift vs. Rockset vs. Teradata Aster vs. XTDB

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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

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

Platform for big data analytics on multistructured data sources and types

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Secondary database models

Relational DBMS
Search engine

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Trend Chart

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

Score	1.07
Rank	#180	Overall
	#31	Document stores

Score	0.13
Rank	#330	Overall
	#45	Document stores

Website

aws.amazon.com/redshift

rockset.com

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

docs.aws.amazon.com/redshift

docs.rockset.com

www.xtdb.com/docs

Developer

Amazon (based on PostgreSQL)

Rockset

Teradata

Juxt Ltd.

Initial release

2012

2019

2005

2019

Current release

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

MIT License

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Clojure

Server operating systems

hosted

Linux

All OS with a Java 8 (and higher) 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

dynamic typing

yes

yes, extensible-data-notation format

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

yes

in Aster File Store

Secondary indexes

restricted

all fields are automatically indexed

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

Read-only SQL queries, including JOINs

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

JDBC
ODBC

HTTP REST

ADO.NET
JDBC
ODBC
OLE DB

HTTP REST
JDBC

Supported programming languages

All languages supporting JDBC/ODBC

Go
Java
JavaScript (Node.js)
Python

C
C#
C++
Java
Python
R

Clojure
Java

Server-side scripts

Stored procedures

user defined functions

in Python

R packages

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic sharding

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

yes, each node contains all data

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

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

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

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

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

fine grained access rights according to SQL-standard

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