DBMS > atoti vs. DolphinDB vs. Graph Engine vs. Qdrant

System Properties Comparison atoti vs. DolphinDB vs. Graph Engine vs. Qdrant

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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.

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

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

Primary database model

Object oriented DBMS

Time Series DBMS

Graph DBMS
Key-value store

Vector DBMS

Secondary database models

Relational DBMS

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

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	1.16
Rank	#175	Overall
	#6	Vector DBMS

Website

atoti.io

www.dolphindb.com

www.graphengine.io

github.com/qdrant/qdrant
qdrant.tech

Technical documentation

docs.atoti.io

docs.dolphindb.cn/en/help200/index.html

www.graphengine.io/docs/manual

qdrant.tech/documentation

Developer

ActiveViam

DolphinDB, Inc

Microsoft

Qdrant

Initial release

2018

2010

2021

Current release

v2.00.4, January 2022

License

Commercial or Open Source

commercial

free versions available

commercial

free community version available

Open Source

MIT License

Open Source

Apache Version 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++

.NET and C

Rust

Server operating systems

Linux
Windows

.NET

Docker
Linux
macOS
Windows

Data scheme

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.

Secondary indexes

yes

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

Multidimensional Expressions (MDX)

SQL-like query language

APIs and other access methods

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

RESTful HTTP API

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

Supported programming languages

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

C#
C++
F#
Visual Basic

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

Server-side scripts

Stored procedures

Python

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Collection-level replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency, tunable consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

Administrators, Users, Groups

Key-based authentication

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More resources

Recent citations in the news

FRTB product of the year: ActiveViam
28 November 2023, Risk.net

provided by Google News

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23 January 2024, TechCrunch

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16 April 2024, Business Wire

Qdrant offers managed vector database for hybrid clouds
16 April 2024, InfoWorld

Qdrant launches first vector database as a managed hybrid cloud
16 April 2024, VentureBeat

Why Vector Data Services For AI Are A Moveable Feast
17 April 2024, Forbes

provided by Google News

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