DBMS > LokiJS vs. Manticore Search vs. Microsoft Azure Cosmos DB vs. Microsoft Azure SQL Database vs. Rockset

System Properties Comparison LokiJS vs. Manticore Search vs. Microsoft Azure Cosmos DB vs. Microsoft Azure SQL Database vs. Rockset

Editorial information provided by DB-Engines

Name

Description

In-memory JavaScript DBMS

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

Globally distributed, horizontally scalable, multi-model database service

Database as a Service offering with high compatibility to Microsoft SQL Server

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Primary database model

Document store

Search engine

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Document store

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

Relational DBMS
Search engine

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

Score	0.43
Rank	#264	Overall
	#42	Document stores

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	0.79
Rank	#211	Overall
	#35	Document stores

Website

github.com/techfort/LokiJS

manticoresearch.com

azure.microsoft.com/services/cosmos-db

azure.microsoft.com/en-us/products/azure-sql/database

rockset.com

Technical documentation

techfort.github.io/LokiJS

manual.manticoresearch.com

learn.microsoft.com/azure/cosmos-db

docs.microsoft.com/en-us/azure/azure-sql

docs.rockset.com

Developer

Manticore Software

Microsoft

Rockset

Initial release

2014

2017

2014

2010

2019

Current release

6.0, February 2023

V12

License

Commercial or Open Source

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

JavaScript

C++

Server operating systems

server-less, requires a JavaScript environment (browser, Node.js)

FreeBSD
Linux
macOS
Windows

hosted

Data scheme

schema-free

Fixed schema

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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

yes

JSON types

yes

dynamic typing

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

yes

ingestion from XML files supported

Secondary indexes

yes

via views

yes

full-text index on all search fields

yes

All properties auto-indexed by default

yes

all fields are automatically indexed

SQL

Support of SQL

SQL-like query language

yes

Read-only SQL queries, including JOINs

APIs and other access methods

JavaScript API

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

Supported programming languages

JavaScript

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

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

View functions in JavaScript

user defined functions

JavaScript

Transact SQL

Triggers

yes

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

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

Sharding

Implicit feature of the cloud service

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Synchronous replication based on Galera library

yes

Implicit feature of the cloud service

yes, with always 3 replicas available

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

none

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

atomic operations within a single collection possible

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

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

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

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

Access rights for users and organizations can be defined via Rockset console

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