DBMS > atoti vs. gStore vs. Qdrant vs. TimescaleDB

System Properties Comparison atoti vs. gStore vs. Qdrant vs. TimescaleDB

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Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

A native Graph DBMS to store and maintain very large RDF datasets.

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

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

Primary database model

Secondary database models

Relational DBMS

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

Score	0.45
Rank	#253	Overall
	#13	Object oriented DBMS

Score	0.03
Rank	#367	Overall
	#37	Graph DBMS
	#18	RDF stores

Score	1.53
Rank	#145	Overall
	#7	Vector DBMS

Score	4.06
Rank	#73	Overall
	#5	Time Series DBMS

Website

atoti.io

en.gstore.cn

github.com/qdrant/qdrant
qdrant.tech

www.timescale.com

Technical documentation

docs.atoti.io

en.gstore.cn/#/enDocs

qdrant.tech/documentation

docs.timescale.com

Developer

ActiveViam

Qdrant

Timescale

Initial release

2016

2021

2017

Current release

1.2, November 2023

2.15.0, May 2024

License

Commercial or Open Source

commercial

free versions available

Open Source

BSD

Open Source

Apache Version 2.0

Open Source

Apache 2.0

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

Java

C++

Rust

Server operating systems

Linux

Docker
Linux
macOS
Windows

Linux
OS X
Windows

Data scheme

schema-free and OWL/RDFS-schema support

schema-free

yes

Typing

predefined data types such as float or date

yes

Numbers, Strings, Geo, Boolean

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

Multidimensional Expressions (MDX)

yes

full PostgreSQL SQL syntax

APIs and other access methods

HTTP API
SPARQL 1.1

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

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

Supported programming languages

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

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

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

Python

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

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

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

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

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

Users, roles and permissions, Role-Based Access Control (RBAC) supported

Key-based authentication

fine grained access rights according to SQL-standard

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