DBMS > Datomic vs. LokiJS vs. Microsoft SQL Server vs. SAP HANA vs. YDB

System Properties Comparison Datomic vs. LokiJS vs. Microsoft SQL Server vs. SAP HANA vs. YDB

Editorial information provided by DB-Engines

Name

Description

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

In-memory JavaScript DBMS

Microsofts flagship relational DBMS

In-memory, column based data store. Available as appliance or cloud service

A distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API

Primary database model

Relational DBMS

Document store

Relational DBMS

Document store
Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	1.55
Rank	#144	Overall
	#67	Relational DBMS

Score	0.44
Rank	#256	Overall
	#40	Document stores

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Score	41.32
Rank	#23	Overall
	#16	Relational DBMS

Score	0.39
Rank	#269	Overall
	#43	Document stores
	#126	Relational DBMS

Website

www.datomic.com

github.com/techfort/LokiJS

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

www.sap.com/products/hana.html

github.com/ydb-platform/ydb
ydb.tech

Technical documentation

docs.datomic.com

techfort.github.io/LokiJS

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

help.sap.com/hana

ydb.tech/en/docs

Developer

Cognitect

Microsoft

SAP

Yandex

Initial release

2012

2014

1989

2010

2019

Current release

1.0.7180, July 2024

SQL Server 2022, November 2022

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

limited edition free

Open Source

commercial

restricted free version is available

commercial

Open Source

Apache 2.0; commercial license available

Cloud-based only

Only available as a cloud service

also available as a cloud based service

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Database as a Service

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Implementation language

Java, Clojure

JavaScript

C++

Server operating systems

All OS with a Java VM

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

Linux
Windows

Appliance or cloud-service

Linux

Data scheme

yes

schema-free

yes

Flexible Schema (defined schema, partial schema, schema free)

Typing

predefined data types such as float or date

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

Secondary indexes

yes

via views

yes

SQL

Support of SQL

yes

SQL-like query language (YQL)

APIs and other access methods

RESTful HTTP API

JavaScript API

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

JDBC
ODBC

RESTful HTTP API (DynamoDB compatible)

Supported programming languages

Clojure
Java

JavaScript

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

Go
Java
JavaScript (Node.js)
PHP
Python

Server-side scripts

Stored procedures

yes

Transaction Functions

View functions in JavaScript

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

SQLScript, R

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

none

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

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

none

yes, but depending on the SQL-Server Edition

yes

Active-passive shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

atomic operations within a single collection possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

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

yes

In-memory capabilities

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

yes

recommended only for testing and development

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes

Access rights defined for Yandex Cloud users

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