DBMS > Badger vs. Blazegraph vs. Sequoiadb vs. Splunk

System Properties Comparison Badger vs. Blazegraph vs. Sequoiadb vs. Splunk

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Editorial information provided by DB-Engines

Name

Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.

Description

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

High-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.

NewSQL database with distributed OLTP and SQL

Analytics Platform for Big Data

Primary database model

Key-value store

Graph DBMS
RDF store

Document store
Relational DBMS

Search engine

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

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

Score	0.81
Rank	#213	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	0.50
Rank	#258	Overall
	#41	Document stores
	#120	Relational DBMS

Score	89.10
Rank	#14	Overall
	#2	Search engines

Website

github.com/dgraph-io/badger

blazegraph.com

www.sequoiadb.com

www.splunk.com

Technical documentation

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

wiki.blazegraph.com

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

docs.splunk.com/Documentation/Splunk

Developer

DGraph Labs

Blazegraph

Sequoiadb Ltd.

Splunk Inc.

Initial release

2017

2006

2013

2003

Current release

2.1.5, March 2019

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

extended commercial license available

Open Source

Server: AGPL; Client: Apache V2

commercial

Limited free edition and free developer edition 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++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Linux

Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

RDF literal types

yes

oid, date, timestamp, binary, regex

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

Secondary indexes

yes

SQL

Support of SQL

SPARQL is used as query language

SQL-like query language

Splunk Search Processing Language for search commands

APIs and other access methods

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

proprietary protocol using JSON

HTTP REST

Supported programming languages

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

.Net
C++
Java
PHP
Python

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Source-replica replication

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in Graphs

Transaction concepts

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

ACID

Document is locked during a transaction

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

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.

User concepts

Access control

Security and Authentication via Web Application Container (Tomcat, Jetty)

simple password-based access control

Access rights for users and roles

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More resources

DB-Engines blog posts

Enterprise Search Engines almost double their popularity in the last 12 months
2 July 2014, Paul Andlinger

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Recent citations in the news

Back to the future: Does graph database success hang on query language?
5 March 2018, ZDNet

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15 December 2015, Datanami

This AI Paper Introduces A Comprehensive RDF Dataset With Over 26 Billion Triples Covering Scholarly Data Across All Scientific Disciplines
19 August 2023, MarkTechPost

Faster with GPUs: 5 turbocharged databases
26 September 2016, InfoWorld

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