DBMS > Databend vs. Microsoft Azure Synapse Analytics

System Properties Comparison Databend vs. Microsoft Azure Synapse Analytics

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Editorial information provided by DB-Engines

Name

Description

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

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

Primary database model

Relational DBMS

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

Score	0.27
Rank	#290	Overall
	#130	Relational DBMS

Score	14.22
Rank	#37	Overall
	#23	Relational DBMS

Website

github.com/datafuselabs/databend
www.databend.com

azure.microsoft.com/services/synapse-analytics

Technical documentation

docs.databend.com

docs.microsoft.com/azure/synapse-analytics

Developer

Databend Labs

Microsoft

Initial release

2021

2016

Current release

1.0.59, April 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

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

Rust

C++

Server operating systems

hosted
Linux
macOS

hosted

Data scheme

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

APIs and other access methods

CLI Client
JDBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

C#
Java
PHP

Server-side scripts

Stored procedures

Transact SQL

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

User concepts

Access control

Users with fine-grained authorization concept, user roles

yes

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