DBMS > CrateDB vs. DolphinDB vs. Greenplum vs. WakandaDB

System Properties Comparison CrateDB vs. DolphinDB vs. Greenplum vs. WakandaDB

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Editorial information provided by DB-Engines

Name

Description

Distributed Database based on Lucene

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

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.

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Time Series DBMS

Relational DBMS

Object oriented 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
	#10	Vector DBMS

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	8.08
Rank	#48	Overall
	#31	Relational DBMS

Score	0.10
Rank	#356	Overall
	#17	Object oriented DBMS

Website

Technical documentation

cratedb.com/docs

docs.dolphindb.cn/en/help200/index.html

docs.greenplum.org

wakanda.github.io/doc

Developer

Crate

DolphinDB, Inc

Pivotal Software Inc.

Wakanda SAS

Initial release

2013

2018

2005

2012

Current release

v2.00.4, January 2022

7.0.0, September 2023

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

commercial

free community version available

Open Source

Apache 2.0

Open Source

AGPLv3, extended commercial license 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

Java

C++

C++, JavaScript

Server operating systems

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

Linux
Windows

Linux

Linux
OS X
Windows

Data scheme

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

yes

Typing

predefined data types such as float or date

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.

yes

since Version 4.2

Secondary indexes

yes

SQL

Support of SQL

yes, but no triggers and constraints, and PostgreSQL compatibility

SQL-like query language

yes

APIs and other access methods

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

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

JDBC
ODBC

RESTful HTTP API

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#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

C
Java
Perl
Python
R

JavaScript

Server-side scripts

Stored procedures

user defined functions (Javascript)

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Configurable replication on table/partition-level

yes

Source-replica replication

none

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

Foreign keys

Referential integrity

yes

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

yes

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

rights management via user accounts

Administrators, Users, Groups

fine grained access rights according to SQL-standard

yes

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More resources

Recent citations in the news

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12 June 2024, AWS Blog

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8 April 2024, Datanami

CrateDB Partners with HiveMQ to Deliver a Seamless Data Management Architecture for IoT
25 March 2024, PR Newswire

How We Designed CrateDB as a Realtime SQL DBMS for the Internet of Things
29 August 2017, The New Stack

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16 May 2017, businesswire.com

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