DBMS > Apache IoTDB vs. InterSystems IRIS vs. Microsoft SQL Server vs. Qdrant

System Properties Comparison Apache IoTDB vs. InterSystems IRIS vs. Microsoft SQL Server vs. Qdrant

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Editorial information provided by DB-Engines

Name

Description

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

A containerised multi-model DBMS, interoperability and analytics data platform with wide capabilities for vertical and horizontal scalability

Microsofts flagship relational DBMS

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

Primary database model

Time Series DBMS

Document store
Key-value store
Object oriented DBMS
Relational DBMS

Relational DBMS

Vector DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	1.31
Rank	#159	Overall
	#14	Time Series DBMS

Score	2.98
Rank	#91	Overall
	#17	Document stores
	#14	Key-value stores
	#1	Object oriented DBMS
	#49	Relational DBMS

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Score	1.53
Rank	#145	Overall
	#7	Vector DBMS

Website

iotdb.apache.org

www.intersystems.com/products/intersystems-iris

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

github.com/qdrant/qdrant
qdrant.tech

Technical documentation

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

docs.intersystems.com/irislatest/csp/docbook/DocBook.UI.Page.cls

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

qdrant.tech/documentation

Developer

Apache Software Foundation

InterSystems

Microsoft

Qdrant

Initial release

2018

1989

2021

Current release

1.1.0, April 2023

2023.3, June 2023

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

restricted free version is available

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C++

Rust

Server operating systems

All OS with a Java VM (>= 1.8)

AIX
Linux
macOS
Ubuntu
Windows

Linux
Windows

Docker
Linux
macOS
Windows

Data scheme

yes

depending on used data model

yes

schema-free

Typing

predefined data types such as float or date

yes

Numbers, Strings, Geo, Boolean

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

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

JDBC
Native API

JDBC
ODBC
RESTful HTTP API

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

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

.Net
C++
Java
JavaScript (Node.js)
Python

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

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

yes

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

Sharding

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

Source-replica replication

yes, but depending on the SQL-Server Edition

Collection-level replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

Eventual Consistency, tunable consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

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

User concepts

Access control

yes

fine grained access rights according to SQL-standard

Key-based authentication

More information provided by the system vendor

Specific characteristics

InterSystems IRIS is a complete cloud-first data platform which includes a multi-model...
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