DBMS > BigObject vs. MonetDB vs. Qdrant vs. TerarkDB

System Properties Comparison BigObject vs. MonetDB vs. Qdrant vs. TerarkDB

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

A relational database management system that stores data in columns

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

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Vector DBMS

Key-value store

Secondary database models

Document store
Spatial DBMS

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

Score	0.13
Rank	#329	Overall
	#147	Relational DBMS

Score	1.72
Rank	#135	Overall
	#62	Relational DBMS

Score	1.53
Rank	#145	Overall
	#7	Vector DBMS

Score	0.00
Rank	#385	Overall
	#61	Key-value stores

Website

bigobject.io

www.monetdb.org

github.com/qdrant/qdrant
qdrant.tech

github.com/bytedance/terarkdb

Technical documentation

docs.bigobject.io

www.monetdb.org/Documentation

qdrant.tech/documentation

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

BigObject, Inc.

MonetDB BV

Qdrant

ByteDance, originally Terark

Initial release

2015

2004

2021

2016

Current release

Dec2023 (11.49), December 2023

License

Commercial or Open Source

commercial

free community edition available

Open Source

Mozilla Public License 2.0

Open Source

Apache Version 2.0

commercial

restricted open source version available

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

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

FreeBSD
Linux
OS X
Solaris
Windows

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

SQL-like DML and DDL statements

yes

SQL 2003 with some extensions

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

C++ API
Java API

Supported programming languages

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

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

C++
Java

Server-side scripts

Stored procedures

Lua

yes, in SQL, C, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding via remote tables

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication available in experimental status

Collection-level replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency, tunable consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

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More resources

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