DBMS > Microsoft Azure Cosmos DB vs. QuestDB vs. Sadas Engine vs. SQLite

System Properties Comparison Microsoft Azure Cosmos DB vs. QuestDB vs. Sadas Engine vs. SQLite

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Editorial information provided by DB-Engines

Name

Description

Globally distributed, horizontally scalable, multi-model database service

A high performance open source SQL database for time series data

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Widely used embeddable, in-process RDBMS

Primary database model

Document store
Graph DBMS
Key-value store
Wide column store

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

Relational DBMS

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

Score	29.85
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	2.48
Rank	#115	Overall
	#9	Time Series DBMS

Score	0.03
Rank	#379	Overall
	#156	Relational DBMS

Score	116.01
Rank	#10	Overall
	#7	Relational DBMS

Website

azure.microsoft.com/services/cosmos-db

questdb.io

www.sadasengine.com

www.sqlite.org

Technical documentation

learn.microsoft.com/azure/cosmos-db

questdb.io/docs

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

www.sqlite.org/docs.html

Developer

Microsoft

QuestDB Technology Inc

SADAS s.r.l.

Dwayne Richard Hipp

Initial release

2014

2006

2000

Current release

8.0

3.45.2 (12 March 2024), March 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

free trial version available

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

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

C++

Server operating systems

hosted

Linux
macOS
Windows

AIX
Linux
Windows

server-less

Data scheme

schema-free

yes

schema-free via InfluxDB Line Protocol

yes

dynamic column types

Typing

predefined data types such as float or date

yes

JSON types

yes

not rigid because of 'dynamic typing' concept.

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.

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

SQL with time-series extensions

yes

SQL-92 is not fully supported

APIs and other access methods

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

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

JDBC
ODBC
Proprietary protocol

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

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

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

over HTTP

.Net
C
C#
C++
Groovy
Java
PHP
Python

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

JavaScript

Triggers

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

horizontal partitioning (by timestamps)

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Source-replica replication with eventual consistency

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

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

Multi-item ACID transactions with snapshot isolation within a partition

ACID for single-table writes

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

Durability

Support for making data persistent

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

managed by 'Learn by Usage'

yes

User concepts

Access control

Access rights can be defined down to the item level

Access rights for users, groups and roles according to SQL-standard

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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