DBMS > LokiJS vs. Microsoft Azure Cosmos DB vs. Microsoft SQL Server vs. Oracle Berkeley DB vs. SingleStore

System Properties Comparison LokiJS vs. Microsoft Azure Cosmos DB vs. Microsoft SQL Server vs. Oracle Berkeley DB vs. SingleStore

Editorial information provided by DB-Engines

Name

Description

In-memory JavaScript DBMS

Globally distributed, horizontally scalable, multi-model database service

Microsofts flagship relational DBMS

Widely used in-process key-value store

MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type

Primary database model

Document store

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

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

Score	0.43
Rank	#264	Overall
	#42	Document stores

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

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Score	5.60
Rank	#62	Overall
	#35	Relational DBMS

Website

github.com/techfort/LokiJS

azure.microsoft.com/services/cosmos-db

www.microsoft.com/en-us/sql-server

www.oracle.com/database/technologies/related/berkeleydb.html

www.singlestore.com

Technical documentation

techfort.github.io/LokiJS

learn.microsoft.com/azure/cosmos-db

learn.microsoft.com/en-US/sql/sql-server

docs.oracle.com/cd/E17076_05/html/index.html

docs.singlestore.com

Developer

Microsoft

Oracle

originally developed by Sleepycat, which was acquired by Oracle

SingleStore Inc.

Initial release

2014

1989

1994

2013

Current release

SQL Server 2022, November 2022

18.1.40, May 2020

8.5, January 2024

License

Commercial or Open Source

Open Source

commercial

restricted free version is available

Open Source

commercial license available

commercial

free developer edition available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

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Implementation language

JavaScript

C++

C, Java, C++ (depending on the Berkeley DB edition)

C++, Go

Server operating systems

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

hosted

Linux
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux

64 bit version required

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

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.

yes

only with the Berkeley DB XML edition

Secondary indexes

yes

via views

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

yes

SQL interfaced based on SQLite is available

yes

but no triggers and foreign keys

APIs and other access methods

JavaScript API

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

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

Supported programming languages

JavaScript

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

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

Bash
C
C#
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

View functions in JavaScript

JavaScript

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes

Triggers

yes

JavaScript

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

tables can be distributed across several files (horizontal partitioning); sharding through federation

none

Sharding

hash partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Implicit feature of the cloud service

yes, but depending on the SQL-Server Edition

Source-replica replication

stores two copies of each physical data partition on two separate nodes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

can define user-defined aggregate functions for map-reduce-style calculations

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

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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.

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

Fine grained access control via users, groups and roles

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

Customers in various industries worldwide including US and International Industry...
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Licensing and pricing models

F ree Tier and Enterprise Edition
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