DBMS > Apache IoTDB vs. Blazegraph vs. InfinityDB vs. Riak KV vs. STSdb

System Properties Comparison Apache IoTDB vs. Blazegraph vs. InfinityDB vs. Riak KV vs. STSdb

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 IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

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

A Java embedded Key-Value Store which extends the Java Map interface

Distributed, fault tolerant key-value store

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Time Series DBMS

Graph DBMS
RDF store

Key-value store

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

Key-value store

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

Score	1.31
Rank	#164	Overall
	#14	Time Series DBMS

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

Score	0.08
Rank	#365	Overall
	#55	Key-value stores

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Website

iotdb.apache.org

blazegraph.com

boilerbay.com

github.com/STSSoft/STSdb4

Technical documentation

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

wiki.blazegraph.com

boilerbay.com/infinitydb/manual

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

Developer

Apache Software Foundation

Blazegraph

Boiler Bay Inc.

OpenSource, formerly Basho Technologies

STS Soft SC

Initial release

2018

2006

2002

2009

2011

Current release

1.1.0, April 2023

2.1.5, March 2019

4.0

3.2.0, December 2022

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

extended commercial license available

commercial

Open Source

Apache version 2, commercial enterprise edition

Open Source

GPLv2, commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Erlang

Server operating systems

All OS with a Java VM (>= 1.8)

Linux
OS X
Windows

All OS with a Java VM

Linux
OS X

Windows

Data scheme

yes

schema-free

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

schema-free

yes

Typing

predefined data types such as float or date

yes

RDF literal types

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

yes

primitive types and user defined types (classes)

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

manual creation possible, using inversions based on multi-value capability

restricted

SQL

Support of SQL

SQL-like query language

SPARQL is used as query language

APIs and other access methods

JDBC
Native API

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

HTTP API
Native Erlang Interface

.NET Client API

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

Java

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

C#
Java

Server-side scripts

Stored procedures

yes

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

Sharding

none

Sharding

no "single point of failure"

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

yes

none

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

READ-COMMITTED or SERIALIZED

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in Graphs

manual creation possible, using inversions based on multi-value capability

links between data sets can be stored

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

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

yes

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

yes, using Riak Security

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