DBMS > Manticore Search vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Synapse Analytics vs. SiteWhere vs. TerminusDB

System Properties Comparison Manticore Search vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Synapse Analytics vs. SiteWhere vs. TerminusDB

Editorial information provided by DB-Engines

Name

Description

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

Globally distributed, horizontally scalable, multi-model database service

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

M2M integration platform for persisting/querying time series data

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Search engine

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Time Series DBMS

Graph DBMS

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

Spatial DBMS

Document store
RDF store

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

Score	0.29
Rank	#302	Overall
	#21	Search engines

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	0.06
Rank	#383	Overall
	#43	Time Series DBMS

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Website

manticoresearch.com

azure.microsoft.com/services/cosmos-db

azure.microsoft.com/services/synapse-analytics

github.com/sitewhere/sitewhere

terminusdb.com

Technical documentation

manual.manticoresearch.com

learn.microsoft.com/azure/cosmos-db

docs.microsoft.com/azure/synapse-analytics

sitewhere1.sitewhere.io/index.html

terminusdb.github.io/terminusdb/#

Developer

Manticore Software

Microsoft

SiteWhere

DataChemist Ltd.

Initial release

2017

2014

2016

2010

2018

Current release

6.0, February 2023

11.0.0, January 2023

License

Commercial or Open Source

Open Source

GPL version 2

commercial

Open Source

Common Public Attribution License Version 1.0

Open Source

GPL V3

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++

Java

Prolog, Rust

Server operating systems

FreeBSD
Linux
macOS
Windows

hosted

Linux
OS X
Windows

Linux

Data scheme

Fixed schema

schema-free

yes

predefined scheme

yes

Typing

predefined data types such as float or date

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

yes

JSON types

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

yes

full-text index on all search fields

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

yes

SQL-like query language (WOQL)

APIs and other access methods

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

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

ADO.NET
JDBC
ODBC

HTTP REST

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

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

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

C#
Java
PHP

JavaScript
Python

Server-side scripts

Stored procedures

user defined functions

JavaScript

Transact SQL

yes

Triggers

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Sharding

Implicit feature of the cloud service

Sharding, horizontal partitioning

Sharding

based on HBase

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication based on Galera library

yes

Implicit feature of the cloud service

yes

selectable replication factor

based on HBase

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

yes

isolated transactions for atomic changes and binary logging for safe writes

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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

yes

in-memory journaling

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

Access rights can be defined down to the item level

yes

Users with fine-grained authorization concept

Role-based access control

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