DBMS > Machbase Neo vs. OushuDB vs. Qdrant vs. SpaceTime vs. Yaacomo

System Properties Comparison Machbase Neo vs. OushuDB vs. Qdrant vs. SpaceTime vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

TimeSeries DBMS for AIoT and BigData

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

SpaceTime is a spatio-temporal DBMS with a focus on performance.

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Secondary database models

Relational DBMS

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

Score	0.17
Rank	#337	Overall
	#30	Time Series DBMS

Score	0.10
Rank	#355	Overall
	#154	Relational DBMS

Score	1.28
Rank	#167	Overall
	#8	Vector DBMS

Score	0.03
Rank	#392	Overall
	#8	Spatial DBMS

Website

machbase.com

www.oushu.com/product/oushuDB

github.com/qdrant/qdrant
qdrant.tech

www.mireo.com/spacetime

yaacomo.com

Technical documentation

machbase.com/dbms

www.oushu.com/documentation

qdrant.tech/documentation

Developer

Machbase

Oushu

Qdrant

Mireo

Q2WEB GmbH

Initial release

2013

2021

2020

2009

Current release

V8.0, August 2023

4.0.1, August 2020

License

Commercial or Open Source

commercial

free test version available

commercial

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Rust

C++

Server operating systems

Linux
macOS
Windows

Linux

Docker
Linux
macOS
Windows

Linux

Android
Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numbers, Strings, Geo, Boolean

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.

Secondary indexes

yes

Keywords, numberic ranges, geo, full-text

yes

SQL

Support of SQL

SQL-like query language

Full-featured ANSI SQL support

A subset of ANSI SQL is implemented

yes

APIs and other access methods

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

JDBC
ODBC

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

RESTful HTTP API

JDBC
ODBC

Supported programming languages

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

C
C++

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

C#
C++
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

Fixed-grid hypercubes

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Collection-level replication

Real-time block device replication (DRBD)

Source-replica replication

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

volatile and lookup table

yes

User concepts

Access control

simple password-based access control

Kerberos, SSL and role based access

Key-based authentication

yes

fine grained access rights according to SQL-standard

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