DBMS > LokiJS vs. Microsoft Azure Cosmos DB vs. Microsoft SQL Server vs. Qdrant vs. XTDB

System Properties Comparison LokiJS vs. Microsoft Azure Cosmos DB vs. Microsoft SQL Server vs. Qdrant vs. XTDB

Editorial information provided by DB-Engines

Name

Description

In-memory JavaScript DBMS

Globally distributed, horizontally scalable, multi-model database service

Microsofts flagship relational DBMS

A high-performance vector database with neural network or semantic-based matching

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Document store

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Vector DBMS

Document store

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	0.49
Rank	#260	Overall
	#42	Document stores

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

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	1.28
Rank	#167	Overall
	#6	Vector DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

github.com/techfort/LokiJS

azure.microsoft.com/services/cosmos-db

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

github.com/qdrant/qdrant
qdrant.tech

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

techfort.github.io/LokiJS

learn.microsoft.com/azure/cosmos-db

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

qdrant.tech/documentation

www.xtdb.com/docs

Developer

Microsoft

Qdrant

Juxt Ltd.

Initial release

2014

1989

2021

2019

Current release

SQL Server 2022, November 2022

1.19, September 2021

License

Commercial or Open Source

Open Source

commercial

restricted free version is available

Open Source

Apache Version 2.0

Open Source

MIT License

Cloud-based only

Only available as a cloud service

yes

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Implementation language

JavaScript

C++

Rust

Clojure

Server operating systems

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

hosted

Linux
Windows

Docker
Linux
macOS
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

yes

Numbers, Strings, Geo, Boolean

yes, extensible-data-notation format

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

All properties auto-indexed by default

yes

Keywords, numberic ranges, geo, full-text

yes

SQL

Support of SQL

SQL-like query language

yes

limited SQL, making use of Apache Calcite

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)

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

HTTP REST
JDBC

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
Go
Java
JavaScript (Node.js)
Python
Rust

Clojure
Java

Server-side scripts

Stored procedures

View functions in JavaScript

JavaScript

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

Triggers

yes

JavaScript

yes

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

Sharding

none

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

Collection-level replication

yes, each node contains all data

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, tunable 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

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

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

Key-based authentication

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