DBMS > Alibaba Cloud AnalyticDB for MySQL vs. Datastax Enterprise vs. RDF4J

System Properties Comparison Alibaba Cloud AnalyticDB for MySQL vs. Datastax Enterprise vs. RDF4J

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

A real-time data warehousing service that can process petabytes of data with high concurrency and low latency. It is fully compatible with the MySQL protocol.

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.

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Relational DBMS

Wide column store

RDF store

Secondary database models

Document store

Document store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS

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

Score	0.85
Rank	#207	Overall
	#96	Relational DBMS

Score	5.80
Rank	#60	Overall
	#4	Wide column stores

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

www.alibabacloud.com/product/analyticdb-for-mysql

www.datastax.com/products/datastax-enterprise

rdf4j.org

Technical documentation

www.alibabacloud.com/help/doc-detail/93776.htm

docs.datastax.com

rdf4j.org/documentation

Developer

Alibaba

DataStax

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2011

2004

Current release

6.8, April 2020

License

Commercial or Open Source

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

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.

Datastax Astra DB: Astra DB simplifies cloud-native Cassandra application development for your apps, microservices and functions. Deploy in minutes on AWS, Google Cloud, Azure, and have it managed for you by the experts, with serverless, pay-as-you-go pricing.

Implementation language

Java

Server operating systems

hosted

Linux
OS X

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free

yes

RDF Schemas

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

Secondary indexes

yes

SQL

Support of SQL

yes

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

APIs and other access methods

JDBC
ODBC

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

C#
Java
PHP
Python

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

Java
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

no "single point of failure"

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

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

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Atomicity and isolation are supported for single operations

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

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

A real-time data warehousing service that can process PB data with high concurrency...
» more

DataStax Enterprise is scale-out data infrastructure for enterprises that need to...
» more

Competitive advantages

TPC Benchmark: The world leading result in TPC-DS benchmark . TPC-H benchmark for...
» more

Supporting the following application requirements: Zero downtime - Built on Apache...
» more

Typical application scenarios

Applications that must be massively and linearly scalable with 100% uptime and able...
» more

Key customers

Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
» more

Market metrics

Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
» more

Licensing and pricing models

Available regions: America US Virginia US Silicon Valley Asia China Hong Kong India...
» more

Annual subscription
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Alibaba Cloud launches new cloud database solutions following market growth
1 October 2020, DataCenterNews Asia

How Data Analytics Capabilities of Alibaba Group Evolve Its Ecosystem to the Cloud
20 February 2021, DataDrivenInvestor

Gartner’s Magic Quadrant for Cloud Database Management Systems
9 December 2020, CRN

Alibaba Cloud Named a Leader in Gartner(R) Magic Quadrant(TM) for Cloud Database Management Systems
8 February 2024, ryt9.com

AWS, IBM, Microsoft, Google emerge Cloud DBMS leaders
22 December 2022, Daily Host News

provided by Google News

DataStax and LlamaIndex Partner to Make Building RAG Applications Easier than Ever for GenAI Developers
20 February 2024, Business Wire

DataStax Introduces Enhanced RAG Capabilities Through Astra DB and NVIDIA Tech
19 March 2024, Datanami

DataStax Rolls Out Vector Search for Astra DB to Support Gen AI
19 July 2023, EnterpriseAI

DataStax adds vector search to boost support for generative AI workloads
18 July 2023, SiliconANGLE News

DataStax goes vector searching with Astra DB – Blocks and Files
20 July 2023, Blocks and Files

provided by Google News

GraphDB Goes Open Source
27 January 2020, iProgrammer

Ontotext's GraphDB 8.10 Makes Knowledge Graph Experience Faster and Richer
13 June 2019, Markets Insider

provided by Google News

Share this page