DBMS > Amazon Redshift vs. Badger vs. Microsoft Azure AI Search vs. Microsoft Azure Synapse Analytics vs. openGemini

System Properties Comparison Amazon Redshift vs. Badger vs. Microsoft Azure AI Search vs. Microsoft Azure Synapse Analytics vs. openGemini

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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

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

An open source distributed Time Series DBMS with high concurrency, high performance, and high scalability

Primary database model

Secondary database models

Vector DBMS

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

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

Score	0.14
Rank	#328	Overall
	#48	Key-value stores

Score	5.75
Rank	#58	Overall
	#7	Search engines

Score	18.98
Rank	#31	Overall
	#19	Relational DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Website

aws.amazon.com/redshift

github.com/dgraph-io/badger

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

azure.microsoft.com/services/synapse-analytics

www.opengemini.org
github.com/openGemini

Technical documentation

docs.aws.amazon.com/redshift

godoc.org/github.com/dgraph-io/badger

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

docs.microsoft.com/azure/synapse-analytics

docs.opengemini.org/guide

Developer

Amazon (based on PostgreSQL)

DGraph Labs

Microsoft

Huawei and openGemini community

Initial release

2012

2017

2015

2016

2022

Current release

1.1, July 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

Apache Version 2.0

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.

Implementation language

C++

Server operating systems

hosted

BSD
Linux
OS X
Solaris
Windows

hosted

Linux
Windows

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

Integer, Float, Boolean, String

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

SQL-like query language

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

ADO.NET
JDBC
ODBC

HTTP REST

Supported programming languages

All languages supporting JDBC/ODBC

C#
Java
JavaScript
Python

C#
Java
PHP

C
C++
Go
Java
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

user defined functions

in Python

Transact SQL

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Implicit feature of the cloud service

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes

Implicit feature of the cloud service

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

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

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

yes

using Azure authentication

yes

Administrators and common users accounts

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