DBMS > Amazon Redshift vs. AntDB vs. Datastax Enterprise vs. Spark SQL

System Properties Comparison Amazon Redshift vs. AntDB vs. Datastax Enterprise vs. Spark SQL

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

A scalable, multi-tenant, MPP-architectured RDBMS for OLTP and OLAP operations, highly compatible with Oracle

DataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Relational DBMS

Wide column store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.25
Rank	#303	Overall
	#137	Relational DBMS

Score	5.80
Rank	#60	Overall
	#4	Wide column stores

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Website

aws.amazon.com/redshift

www.asiainfo.com/en_us/product_aisware_antdb_detail.html

www.datastax.com/products/datastax-enterprise

spark.apache.org/sql

Technical documentation

docs.aws.amazon.com/redshift

docs.datastax.com

spark.apache.org/docs/latest/sql-programming-guide.html

Social network pages

Developer

Amazon (based on PostgreSQL)

AsiaInfo Technologies Limited

DataStax

Apache Software Foundation

Initial release

2012

2011

2014

Current release

6.8, April 2020

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

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.

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Implementation language

Java

Scala

Server operating systems

hosted

Linux
OS X

Linux
OS X
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.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL2016 compliant

SQL-like DML and DDL statements (CQL); Spark SQL

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC

JDBC
MySQL protocol compliant
ODBC

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

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

Java
Python
R
Scala

Server-side scripts

Stored procedures

user defined functions

in Python

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

yes

configurable replication factor, datacenter aware, advanced replication for edge computing

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
Tunable Consistency

consistency level can be individually decided with each write operation

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

Atomicity and isolation are supported for single operations

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

Access rights for users can be defined per object

More information provided by the system vendor

Specific characteristics

AntDB was initiated in 2008. On the core system of operators, AntDB provides online...
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DataStax Enterprise is scale-out data infrastructure for enterprises that need to...
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Competitive advantages

HTAP mixed load: AntDB is a universal, enterprise-level distributed relational database,...
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Supporting the following application requirements: Zero downtime - Built on Apache...
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Typical application scenarios

As the core software of large enterprise, AntDB supports multi-scenario deployment....
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Applications that must be massively and linearly scalable with 100% uptime and able...
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Key customers

China Mobile, China Telecom, China Unicom, Aeon Life, China Mobile Tietong, CITIC...
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Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
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Market metrics

More than 1 billion subscribers in 24 provinces across China are served by AntDB...
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Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
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Licensing and pricing models

Certificates and licenses CMMI5 Certificate licensed by CMMI Institute IT Product...
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Annual subscription
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