DBMS > Blueflood vs. Citus vs. LevelDB vs. Riak KV vs. Stardog

System Properties Comparison Blueflood vs. Citus vs. LevelDB vs. Riak KV vs. Stardog

Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

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

Distributed, fault tolerant key-value store

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Time Series DBMS

Relational DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Graph DBMS
RDF store

Secondary database models

Document store

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

Score	0.06
Rank	#352	Overall
	#36	Time Series DBMS

Score	2.13
Rank	#117	Overall
	#56	Relational DBMS

Score	2.33
Rank	#111	Overall
	#19	Key-value stores

Score	3.84
Rank	#76	Overall
	#9	Key-value stores

Score	1.93
Rank	#121	Overall
	#10	Graph DBMS
	#6	RDF stores

Website

blueflood.io

www.citusdata.com

github.com/google/leveldb

www.stardog.com

Technical documentation

github.com/rax-maas/blueflood/wiki

docs.citusdata.com

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

www.tiot.jp/riak-docs/riak/kv/latest

docs.stardog.com

Developer

Rackspace

Google

OpenSource, formerly Basho Technologies

Stardog-Union

Initial release

2013

2010

2011

2009

2010

Current release

8.1, December 2018

1.23, February 2021

3.2.0, December 2022

7.3.0, May 2020

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

AGPL, commercial license also available

Open Source

BSD

Open Source

Apache version 2, commercial enterprise edition

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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++

Erlang

Java

Server operating systems

Linux
OS X

Linux

Illumos
Linux
OS X
Windows

Linux
OS X

Linux
macOS
Windows

Data scheme

predefined scheme

yes

schema-free

schema-free and OWL/RDFS-schema support

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

specific XML type available, but no XML query functionality

Import/export of XML data possible

Secondary indexes

yes

restricted

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

yes

standard, with numerous extensions

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

HTTP REST

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

HTTP API
Native Erlang Interface

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Erlang

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

pre-commit hooks and post-commit hooks

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

none

Sharding

no "single point of failure"

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Source-replica replication

other methods possible by using 3rd party extensions

none

selectable replication factor

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Eventual Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

links between data sets can be stored

yes

relationships in graphs

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

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

yes, using Riak Security

Access rights for users and roles

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