DBMS > Amazon Redshift vs. Dolt vs. HBase vs. Microsoft Azure AI Search vs. Microsoft Azure Synapse Analytics

System Properties Comparison Amazon Redshift vs. Dolt vs. HBase vs. Microsoft Azure AI Search vs. Microsoft Azure Synapse Analytics

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

A MySQL compatible DBMS with Git-like versioning of data and schema

Wide-column store based on Apache Hadoop and on concepts of BigTable

Search-as-a-service for web and mobile app development

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

Primary database model

Secondary database models

Document store

Vector DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	1.02
Rank	#191	Overall
	#89	Relational DBMS

Score	27.97
Rank	#26	Overall
	#2	Wide column stores

Score	5.52
Rank	#59	Overall
	#6	Search engines

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Website

aws.amazon.com/redshift

github.com/dolthub/dolt
www.dolthub.com

hbase.apache.org

azure.microsoft.com/en-us/services/search

azure.microsoft.com/services/synapse-analytics

Technical documentation

docs.aws.amazon.com/redshift

docs.dolthub.com

hbase.apache.org/book.html

learn.microsoft.com/en-us/azure/search

docs.microsoft.com/azure/synapse-analytics

Developer

Amazon (based on PostgreSQL)

DoltHub Inc

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Microsoft

Initial release

2012

2018

2008

2015

2016

Current release

2.3.4, January 2021

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache version 2

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

hosted

Linux
macOS
Windows

Linux
Unix
Windows

using Cygwin

hosted

Data scheme

yes

schema-free, schema definition possible

yes

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

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

yes

APIs and other access methods

JDBC
ODBC

CLI Client
HTTP REST

Java API
RESTful HTTP API
Thrift

RESTful HTTP API

ADO.NET
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C
C#
C++
Groovy
Java
PHP
Python
Scala

C#
Java
JavaScript
Python

C#
Java
PHP

Server-side scripts

Stored procedures

user defined functions

in Python

yes

currently in alpha release

yes

Coprocessors in Java

Transact SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Implicit feature of the cloud service

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

A database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.

Multi-source replication
Source-replica replication

yes

Implicit feature of the cloud service

yes

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 or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

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

ACID

Single row ACID (across millions of columns)

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

fine grained access rights according to SQL-standard

Only one user is configurable, and must be specified in the config file at startup

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

yes

using Azure authentication

yes

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