DBMS > LokiJS vs. Microsoft Azure SQL Database vs. QuestDB vs. SAP HANA

System Properties Comparison LokiJS vs. Microsoft Azure SQL Database vs. QuestDB vs. SAP HANA

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Editorial information provided by DB-Engines

Name

Description

In-memory JavaScript DBMS

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

A high performance open source SQL database for time series data

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

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Relational 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	0.43
Rank	#264	Overall
	#42	Document stores

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	2.52
Rank	#109	Overall
	#9	Time Series DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

github.com/techfort/LokiJS

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

questdb.io

www.sap.com/products/hana.html

Technical documentation

techfort.github.io/LokiJS

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

questdb.io/docs

help.sap.com/hana

Developer

Microsoft

QuestDB Technology Inc

SAP

Initial release

2014

2010

2014

2010

Current release

V12

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

commercial

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

JavaScript

C++

Java (Zero-GC), C++, Rust

Server operating systems

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

hosted

Linux
macOS
Windows

Appliance or cloud-service

Data scheme

schema-free

yes

schema-free via InfluxDB Line Protocol

yes

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 with time-series extensions

yes

APIs and other access methods

JavaScript API

ADO.NET
JDBC
ODBC

HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol

JDBC
ODBC

Supported programming languages

JavaScript

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

PostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust

over HTTP

Server-side scripts

Stored procedures

View functions in JavaScript

Transact SQL

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning (by timestamps)

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes, with always 3 replicas available

Source-replica replication with eventual consistency

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

ACID

ACID for single-table writes

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

In-memory capabilities

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

yes

through memory mapped files

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes

More information provided by the system vendor

Specific characteristics

Relational model with native time series support Column-based storage and time partitioned...
» more

Competitive advantages

High ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more

Typical application scenarios

Financial tick data Industrial IoT Application Metrics Monitoring
» more

Key customers

Banks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more

Licensing and pricing models

Open source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more

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5 April 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.