DBMS > Amazon Redshift vs. CockroachDB vs. Qdrant vs. RethinkDB vs. Yaacomo

System Properties Comparison Amazon Redshift vs. CockroachDB vs. Qdrant vs. RethinkDB vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

Large scale data warehouse service for use with business intelligence tools

CockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.

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

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Secondary database models

Spatial DBMS

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

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

Score	4.74
Rank	#67	Overall
	#36	Relational DBMS

Score	1.53
Rank	#145	Overall
	#7	Vector DBMS

Score	2.58
Rank	#105	Overall
	#20	Document stores

Website

aws.amazon.com/redshift

www.cockroachlabs.com

github.com/qdrant/qdrant
qdrant.tech

rethinkdb.com

yaacomo.com

Technical documentation

docs.aws.amazon.com/redshift

www.cockroachlabs.com/docs

qdrant.tech/documentation

rethinkdb.com/docs

Developer

Amazon (based on PostgreSQL)

Cockroach Labs

Qdrant

The Linux Foundation

since July 2017

Q2WEB GmbH

Initial release

2012

2015

2021

2009

Current release

24.1.0, May 2024

2.4.1, August 2020

License

Commercial or Open Source

commercial

Open Source

Apache 2.0, commercial license available

Open Source

Apache Version 2.0

Open Source

Apache Version 2

commercial

Cloud-based only

Only available as a cloud service

yes

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

hosted

Linux
macOS
Windows

Docker
Linux
macOS
Windows

Linux
OS X
Windows

Android
Linux
Windows

Data scheme

yes

dynamic schema

schema-free

yes

Typing

predefined data types such as float or date

yes

Numbers, Strings, Geo, Boolean

yes

string, binary, float, bool, date, geometry

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

restricted

yes

Keywords, numberic ranges, geo, full-text

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes, wire compatible with PostgreSQL

yes

APIs and other access methods

JDBC
ODBC

JDBC

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

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

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

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

Server-side scripts

Stored procedures

user defined functions

in Python

Triggers

Client-side triggers through changefeeds

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by key range)

all tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFT

Sharding

range based

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication using RAFT

Collection-level replication

Source-replica 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

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

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

Role-based access control

Key-based authentication

yes

users and table-level permissions

fine grained access rights according to SQL-standard

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