DBMS > CrateDB vs. Microsoft Azure Synapse Analytics vs. TDSQL for MySQL

System Properties Comparison CrateDB vs. Microsoft Azure Synapse Analytics vs. TDSQL for MySQL

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Editorial information provided by DB-Engines

Name

Description

Distributed Database based on Lucene

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

A high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.

Primary database model

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Relational DBMS

Secondary database models

Relational DBMS

Document store
Spatial DBMS

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

Score	0.72
Rank	#222	Overall
	#37	Document stores
	#5	Spatial DBMS
	#15	Search engines
	#18	Time Series DBMS
	#10	Vector DBMS

Score	19.84
Rank	#31	Overall
	#19	Relational DBMS

Score	0.84
Rank	#204	Overall
	#94	Relational DBMS

Website

cratedb.com

azure.microsoft.com/services/synapse-analytics

www.tencentcloud.com/products/dcdb

Technical documentation

cratedb.com/docs

docs.microsoft.com/azure/synapse-analytics

www.tencentcloud.com/document/product/1042

Developer

Crate

Microsoft

Tencent

Initial release

2013

2016

2013

License

Commercial or Open Source

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++

Server operating systems

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

hosted

Data scheme

Flexible Schema (defined schema, partial schema, 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

yes

SQL

Support of SQL

yes, but no triggers and constraints, and PostgreSQL compatibility

yes

APIs and other access methods

ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

ADO.NET
JDBC
ODBC

JDBC
ODBC

Supported programming languages

.NET
Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
R
Ruby

community maintained client
Scala

community maintained client

C#
Java
PHP

C
C#
C++
Java
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions (Javascript)

Transact SQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Configurable replication on table/partition-level

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Read-after-write consistency on record level

Immediate Consistency

Foreign keys

Referential integrity

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

unique row identifiers can be used for implementing an optimistic concurrency control strategy

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.

User concepts

Access control

rights management via user accounts

yes

Users with fine-grained authorization concept

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More resources

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