DBMS > CrateDB vs. Greenplum vs. MySQL vs. Qdrant

System Properties Comparison CrateDB vs. Greenplum vs. MySQL vs. Qdrant

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Editorial information provided by DB-Engines

Name

Description

Distributed Database based on Lucene

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

Widely used open source RDBMS

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

Primary database model

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Relational DBMS

Key/Value like access via memcached API

Vector DBMS

Secondary database models

Relational DBMS

Document store
Spatial DBMS

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

Score	0.71
Rank	#227	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#8	Vector DBMS

Score	8.08
Rank	#48	Overall
	#31	Relational DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	1.28
Rank	#167	Overall
	#6	Vector DBMS

Website

cratedb.com

greenplum.org

www.mysql.com

github.com/qdrant/qdrant
qdrant.tech

Technical documentation

cratedb.com/docs

docs.greenplum.org

dev.mysql.com/doc

qdrant.tech/documentation

Developer

Crate

Pivotal Software Inc.

Oracle

since 2010, originally MySQL AB, then Sun

Qdrant

Initial release

2013

2005

1995

2021

Current release

7.0.0, September 2023

8.4.0, April 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

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.

CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.

Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.

Implementation language

Java

C and C++

Rust

Server operating systems

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

Linux

FreeBSD
Linux
OS X
Solaris
Windows

Docker
Linux
macOS
Windows

Data scheme

Flexible Schema (defined schema, partial schema, schema free)

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.

yes

since Version 4.2

yes

Secondary indexes

yes

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

yes, but no triggers and constraints, and PostgreSQL compatibility

yes

with proprietary extensions

APIs and other access methods

ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

Supported programming languages

.NET
Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
R
Ruby

community maintained client
Scala

community maintained client

C
Java
Perl
Python
R

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

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

Server-side scripts

Stored procedures

user defined functions (Javascript)

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Configurable replication on table/partition-level

Source-replica replication

Multi-source replication
Source-replica replication

Collection-level replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Read-after-write consistency on record level

Immediate Consistency

Eventual Consistency, tunable consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

unique row identifiers can be used for implementing an optimistic concurrency control strategy

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

rights management via user accounts

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

Key-based authentication

More information provided by the system vendor

Specific characteristics

The enterprise database for time series, documents, and vectors. Distributed - Native...
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Competitive advantages

Response time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
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Typical application scenarios

IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
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Key customers

Across all continents, CrateDB is used by companies of all sizes to meet the most...
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Market metrics

The CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
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Licensing and pricing models

See CrateDB pricing >
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.