DBMS > Apache Drill vs. Atos Standard Common Repository vs. Kingbase vs. Qdrant

System Properties Comparison Apache Drill vs. Atos Standard Common Repository vs. Kingbase vs. Qdrant

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.

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

Primary database model

Document store
Relational DBMS

Document store
Key-value store

Relational DBMS

Vector DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	1.95
Rank	#127	Overall
	#23	Document stores
	#60	Relational DBMS

Score	0.45
Rank	#262	Overall
	#123	Relational DBMS

Score	1.16
Rank	#175	Overall
	#6	Vector DBMS

Website

drill.apache.org

atos.net/en/convergence-creators/portfolio/standard-common-repository

www.kingbase.com.cn

github.com/qdrant/qdrant
qdrant.tech

Technical documentation

drill.apache.org/docs

qdrant.tech/documentation

Developer

Apache Software Foundation

Atos Convergence Creators

BeiJing KINGBASE Information technologies inc.

Qdrant

Initial release

2012

2016

1999

2021

Current release

1.20.3, January 2023

1703

V8.0, August 2021

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

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 and Java

Rust

Server operating systems

Linux
OS X
Windows

Linux

Linux
Windows

Docker
Linux
macOS
Windows

Data scheme

schema-free

Schema and schema-less with LDAP views

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

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.

yes

Secondary indexes

yes

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

Standard with numerous extensions

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

LDAP

ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

Supported programming languages

C++

All languages with LDAP bindings

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

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

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

horizontal partitioning (by range, list and hash) and vertical 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

none

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency, tunable consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

Depending on the underlying data source

yes

User concepts

Access control

Depending on the underlying data source

LDAP bind authentication

fine grained access rights according to SQL-standard

Key-based authentication

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Apache Drill case study: A tutorial on processing CSV files
9 June 2016, TheServerSide.com

Analyse Kafka messages with SQL queries using Apache Drill
23 September 2019, Towards Data Science

Apache Drill improves big data SQL query engine
31 August 2021, TechTarget

Apache Drill Eliminates ETL, Data Transformation for MapR Database
11 April 2016, The New Stack

Apache Drill Poised to Crack Tough Data Challenges
19 May 2015, Datanami

provided by Google News

Made in China 2025 is back, with a new name and a focus on database companies – The China Project
19 December 2022, The China Project

Opening preparation - Alekhine defense, Saemisch variation
18 April 2016, Chess.com

Backup & Recovery Solutions from China
4 August 2022, Хабр

provided by Google News

Open source vector database startup Qdrant raises $28M
23 January 2024, TechCrunch

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

Qdrant Hybrid Cloud is Now Available for OCI Customers: Managed Vector Search Engine for Data-Sensitive AI ...
16 April 2024, blogs.oracle.com

Qdrant Announces an Industry-First Hybrid Cloud Offering For Enterprise AI Applications
16 April 2024, businesswire.com

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

provided by Google News

Share this page