DBMS > Datastax Enterprise vs. Galaxybase vs. Microsoft Azure Synapse Analytics

System Properties Comparison Datastax Enterprise vs. Galaxybase vs. Microsoft Azure Synapse Analytics

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Editorial information provided by DB-Engines

Name

Description

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.

Scalable, ACID-compliant native distributed parallel graph platform

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Primary database model

Wide column store

Graph DBMS

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	3.89
Rank	#69	Overall
	#4	Wide column stores

Score	0.00
Rank	#394	Overall
	#42	Graph DBMS

Score	14.19
Rank	#38	Overall
	#23	Relational DBMS

Website

www.datastax.com/products/datastax-enterprise

galaxybase.com

azure.microsoft.com/services/synapse-analytics

Technical documentation

docs.datastax.com

docs.microsoft.com/azure/synapse-analytics

Developer

DataStax

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

Microsoft

Initial release

2011

2017

2016

Current release

6.8, April 2020

Nov 20, November 2021

License

Commercial or Open Source

commercial

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

C and Java

C++

Server operating systems

Linux
OS X

Linux

hosted

Data scheme

schema-free

Strong typed schema

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

yes

SQL

Support of SQL

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

yes

APIs and other access methods

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

ADO.NET
JDBC
ODBC

Supported programming languages

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

Go
Java
Python

C#
Java
PHP

Server-side scripts

Stored procedures

user defined procedures and functions

Transact SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

consistency level can be individually decided with each write operation

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

Transaction concepts

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

Atomicity and isolation are supported for single operations

ACID

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

Access rights for users can be defined per object

Role-based access control

yes

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More resources

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