DBMS > Amazon Redshift vs. EJDB vs. Manticore Search vs. Microsoft Azure AI Search vs. Microsoft Azure Synapse Analytics

System Properties Comparison Amazon Redshift vs. EJDB vs. Manticore Search 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

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Multi-storage database for search, including full-text search.

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

Time Series DBMS

using the Manticore Columnar Library

Vector DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	0.29
Rank	#302	Overall
	#21	Search engines

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/Softmotions/ejdb

manticoresearch.com

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

azure.microsoft.com/services/synapse-analytics

Technical documentation

docs.aws.amazon.com/redshift

github.com/Softmotions/ejdb/blob/master/README.md

manual.manticoresearch.com

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

docs.microsoft.com/azure/synapse-analytics

Developer

Amazon (based on PostgreSQL)

Softmotions

Manticore Software

Microsoft

Initial release

2012

2017

2015

2016

Current release

6.0, February 2023

License

Commercial or Open Source

commercial

Open Source

GPLv2

Open Source

GPL 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

C++

Server operating systems

hosted

server-less

FreeBSD
Linux
macOS
Windows

hosted

Data scheme

yes

schema-free

Fixed schema

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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.

Can index from XML

Secondary indexes

restricted

yes

full-text index on all search fields

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC

in-process shared library

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

RESTful HTTP API

ADO.NET
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

C#
Java
JavaScript
Python

C#
Java
PHP

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

Transact SQL

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

Sharding

Implicit feature of the cloud service

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Synchronous replication based on Galera library

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

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

typically not needed, however similar functionality with collection joins possible

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

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Manticore index.

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

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.