DBMS > Atos Standard Common Repository vs. Blueflood vs. Brytlyt vs. ClickHouse vs. Qdrant

System Properties Comparison Atos Standard Common Repository vs. Blueflood vs. Brytlyt vs. ClickHouse vs. Qdrant

Editorial information provided by DB-Engines

Name

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

Description

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

Scalable TimeSeries DBMS based on Cassandra

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

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

Primary database model

Document store
Key-value store

Time Series DBMS

Relational DBMS

Vector DBMS

Secondary database models

Time Series DBMS

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

Score	0.13
Rank	#346	Overall
	#33	Time Series DBMS

Score	0.38
Rank	#276	Overall
	#127	Relational DBMS

Score	15.55
Rank	#38	Overall
	#23	Relational DBMS

Score	1.28
Rank	#167	Overall
	#6	Vector DBMS

Website

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

blueflood.io

brytlyt.io

clickhouse.com

github.com/qdrant/qdrant
qdrant.tech

Technical documentation

github.com/rax-maas/blueflood/wiki

docs.brytlyt.io

clickhouse.com/docs

qdrant.tech/documentation

Developer

Atos Convergence Creators

Rackspace

Brytlyt

Clickhouse Inc.

Qdrant

Initial release

2016

2013

2016

2021

Current release

1703

5.0, August 2023

v24.4.1.2088-stable, May 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

Apache 2.0

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.

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Implementation language

Java

C, C++ and CUDA

C++

Rust

Server operating systems

Linux

Linux
OS X

Linux
OS X
Windows

FreeBSD
Linux
macOS

Docker
Linux
macOS
Windows

Data scheme

Schema and schema-less with LDAP views

predefined scheme

yes

schema-free

Typing

predefined data types such as float or date

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

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

yes

Close to ANSI SQL (SQL/JSON + extensions)

APIs and other access methods

LDAP

HTTP REST

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

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

Supported programming languages

All languages with LDAP bindings

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

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

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

based on Cassandra

key based and custom

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on Cassandra

Source-replica replication

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

Collection-level replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

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

LDAP bind authentication

fine grained access rights according to SQL-standard

Access rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

Key-based authentication

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