DBMS > BigchainDB vs. CrateDB vs. LevelDB vs. RDF4J vs. Sequoiadb

System Properties Comparison BigchainDB vs. CrateDB vs. LevelDB vs. RDF4J vs. Sequoiadb

Editorial information provided by DB-Engines

Name

Description

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

Distributed Date Store based on Lucene

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

NewSQL database with distributed OLTP and SQL

Primary database model

Document store

Relational DBMS
Search engine

Key-value store

RDF store

Document store
Relational DBMS

Secondary database models

Document store

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

Score	0.75
Rank	#199	Overall
	#30	Document stores

Score	0.75
Rank	#197	Overall
	#100	Relational DBMS
	#12	Search engines

Score	2.76
Rank	#98	Overall
	#18	Key-value stores

Score	0.54
Rank	#225	Overall
	#9	RDF stores

Score	0.38
Rank	#254	Overall
	#37	Document stores
	#117	Relational DBMS

Website

www.bigchaindb.com

crate.io

github.com/google/leveldb

rdf4j.org

www.sequoiadb.com

Technical documentation

bigchaindb.readthedocs.io/en/latest

crate.io/docs

github.com/google/leveldb/blob/master/doc/index.md

rdf4j.org/documentation

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Crate

Google

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Sequoiadb Ltd.

Initial release

2016

2013

2011

2004

2013

Current release

1.23 , February 2021

License

Commercial or Open Source

Open Source

AGPL v3

Open Source

BSD

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Server: AGPL; Client: Apache V2

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

Python

Java

C++

Java

C++

Server operating systems

Linux

All OS with a Java 7 (and higher) VM

Illumos
Linux
OS X
Windows

Linux
OS X
Unix
Windows

Linux

Data scheme

schema-free

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

schema-free

yes

RDF Schemas

schema-free

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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

SQL-like query language

APIs and other access methods

CLI Client
RESTful HTTP API

ADO.NET

community maintained client
JDBC
MQTT (Message Queue Telemetry Transport)
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

proprietary protocol using JSON

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
Ruby

community maintained client
Scala

community maintained client

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

Java
PHP
Python

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

yes

JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Read Your Own Writes Consistency

for primary key lookups

Immediate Consistency

Eventual 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

ACID

Isolation support depends on the API used

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

yes

with automatic compression on writes

yes

in-memory storage is supported as well

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

yes

rights management via user accounts

simple password-based access control

More information provided by the system vendor

Specific characteristics

CrateDB is an open source distributed SQL database that spreads data and processing...
» more

Competitive advantages

CrateDB is typically used in operational analytics applications, particularly those...
» more

Typical application scenarios

CrateDB is ideal for integrating and analyzing streams of data--often machine-generated--in...
» more

Key customers

CrateDB customers include McAfee, Qualtrics , Nokia, NBC Golfnow , Digital Domain...
» more

Market metrics

The CrateDB open source project was started in 2014. CrateDB was the winner of TechCrunch...
» more

Licensing and pricing models

CrateDB pricing CrateDB Community Edition is open source and free to use under the...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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