DBMS > OushuDB vs. Qdrant vs. TempoIQ vs. TimescaleDB

System Properties Comparison OushuDB vs. Qdrant vs. TempoIQ vs. TimescaleDB

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Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

Description

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

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

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Relational DBMS

Vector DBMS

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	0.05
Rank	#357	Overall
	#151	Relational DBMS

Score	1.53
Rank	#145	Overall
	#7	Vector DBMS

Score	4.06
Rank	#73	Overall
	#5	Time Series DBMS

Website

www.oushu.com/product/oushuDB

github.com/qdrant/qdrant
qdrant.tech

tempoiq.com (offline)

www.timescale.com

Technical documentation

www.oushu.com/documentation

qdrant.tech/documentation

docs.timescale.com

Developer

Oushu

Qdrant

TempoIQ

Timescale

Initial release

2021

2012

2017

Current release

4.0.1, August 2020

2.15.0, May 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Rust

Server operating systems

Linux

Docker
Linux
macOS
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numbers, Strings, Geo, Boolean

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

yes

SQL

Support of SQL

Full-featured ANSI SQL support

yes

full PostgreSQL SQL syntax

APIs and other access methods

JDBC
ODBC

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

C
C++

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

C#
Java
JavaScript

Node.js
Python
Ruby

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

Realtime Alerts

yes

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

Collection-level replication

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency, tunable consistency

Immediate 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

Kerberos, SSL and role based access

Key-based authentication

simple authentication-based access control

fine grained access rights according to SQL-standard

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