DBMS > Badger vs. CrateDB vs. DolphinDB vs. FatDB

System Properties Comparison Badger vs. CrateDB vs. DolphinDB vs. FatDB

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Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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.

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Primary database model

Key-value store

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Time Series DBMS

Document store
Key-value store

Secondary database models

Relational DBMS

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

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

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

Website

github.com/dgraph-io/badger

cratedb.com

www.dolphindb.com

Technical documentation

godoc.org/github.com/dgraph-io/badger

cratedb.com/docs

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

Developer

DGraph Labs

Crate

DolphinDB, Inc

FatCloud

Initial release

2017

2013

2018

2012

Current release

v2.00.4, January 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

commercial

free community version available

commercial

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++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

Linux
Windows

Windows

Data scheme

schema-free

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

yes

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

yes, but no triggers and constraints, and PostgreSQL compatibility

SQL-like query language

Via inetgration in SQL Server

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

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

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

Server-side scripts

Stored procedures

user defined functions (Javascript)

yes

via applications

Triggers

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Configurable replication on table/partition-level

yes

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Read-after-write consistency on record level

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

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

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

Can implement custom security layer via applications

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More resources

Recent citations in the news

AWS Marketplace: CrateDB Cloud Comments
12 June 2024, AWS Blog

CrateDB Announces Availability of CrateDB on Google Cloud Marketplace
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

Crate.io Introduces CrateDB 2.0 Enterprise and Open Source Editions
16 May 2017, businesswire.com

provided by Google News

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