DBMS > atoti vs. BoltDB vs. Cubrid vs. Qdrant vs. Transbase

System Properties Comparison atoti vs. BoltDB vs. Cubrid vs. Qdrant vs. Transbase

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.

An embedded key-value store for Go.

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

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

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

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

Score	0.61
Rank	#243	Overall
	#10	Object oriented DBMS

Score	0.80
Rank	#215	Overall
	#31	Key-value stores

Score	1.04
Rank	#187	Overall
	#87	Relational DBMS

Score	1.28
Rank	#167	Overall
	#6	Vector DBMS

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Website

atoti.io

github.com/boltdb/bolt

cubrid.com (korean)
cubrid.org (english)

github.com/qdrant/qdrant
qdrant.tech

www.transaction.de/en/products/transbase.html

Technical documentation

docs.atoti.io

cubrid.org/manuals

qdrant.tech/documentation

www.transaction.de/en/products/transbase/features.html

Developer

ActiveViam

CUBRID Corporation, CUBRID Foundation

Qdrant

Transaction Software GmbH

Initial release

2013

2008

2021

1987

Current release

11.0, January 2021

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

free versions available

Open Source

MIT License

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

commercial

free development license

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, C++, Java

Rust

C and C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
Windows

Docker
Linux
macOS
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

schema-free

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

Multidimensional Expressions (MDX)

yes

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

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

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

Python

Java Stored Procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

Collection-level replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

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

yes

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

fine grained access rights according to SQL-standard

Key-based authentication

fine grained access rights according to SQL-standard

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More resources

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