DBMS > Apache Pinot vs. Blazegraph vs. ReductStore vs. SWC-DB

System Properties Comparison Apache Pinot vs. Blazegraph vs. ReductStore vs. SWC-DB

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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

Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency

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

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

A high performance, scalable Wide Column DBMS

Primary database model

Secondary database models

Time Series DBMS

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

Score	0.40
Rank	#270	Overall
	#125	Relational DBMS

Score	0.75
Rank	#219	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

pinot.apache.org

blazegraph.com

github.com/reductstore
www.reduct.store

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

docs.pinot.apache.org

wiki.blazegraph.com

www.reduct.store/docs

Developer

Apache Software Foundation and contributors

Blazegraph

ReductStore LLC

Alex Kashirin

Initial release

2015

2006

2023

2020

Current release

1.0.0, September 2023

2.1.5, March 2019

1.9, March 2024

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

extended commercial license available

Open Source

Business Source License 1.1

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++, Rust

C++

Server operating systems

All OS with a Java JDK11 or higher

Linux
OS X
Windows

Docker
Linux
macOS
Windows

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

RDF literal types

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

SQL-like query language

SPARQL is used as query language

SQL-like query language

APIs and other access methods

JDBC

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

HTTP API

Proprietary protocol
Thrift

Supported programming languages

Go
Java
Python

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

C++
JavaScript (Node.js)
Python
Rust

C++

Server-side scripts

Stored procedures

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

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

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)

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More resources

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