DBMS > Apache IoTDB vs. Blazegraph vs. GigaSpaces vs. Oracle NoSQL

System Properties Comparison Apache IoTDB vs. Blazegraph vs. GigaSpaces vs. Oracle NoSQL

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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 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.

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Primary database model

Time Series DBMS

Graph DBMS
RDF store

Document store
Object oriented DBMS

Values are user defined objects

Document store
Key-value store
Relational DBMS

Secondary database models

Graph DBMS
Search engine

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

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

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

Score	0.97
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Website

iotdb.apache.org

blazegraph.com

www.gigaspaces.com

www.oracle.com/database/nosql/technologies/nosql

Technical documentation

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

wiki.blazegraph.com

docs.gigaspaces.com/latest/landing.html

docs.oracle.com/en/database/other-databases/nosql-database/index.html

Developer

Apache Software Foundation

Blazegraph

Gigaspaces Technologies

Oracle

Initial release

2018

2006

2000

2011

Current release

1.1.0, April 2023

2.1.5, March 2019

15.5, September 2020

23.3, December 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

extended commercial license available

Open Source

Apache Version 2; Commercial licenses available

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Java, C++, .Net

Java

Server operating systems

All OS with a Java VM (>= 1.8)

Linux
OS X
Windows

Linux
macOS
Solaris
Windows

Linux
Solaris SPARC/x86

Data scheme

yes

schema-free

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

Typing

predefined data types such as float or date

yes

RDF literal types

yes

optional

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.

XML can be used for describing objects metadata

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

SPARQL is used as query language

SQL-99 for query and DML statements

SQL-like DML and DDL statements

APIs and other access methods

JDBC
Native API

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

RESTful HTTP API

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

.Net
C++
Java
Python
Scala

C
C#
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

yes, event driven architecture

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

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

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

yes

Map-Reduce pattern can be built with XAP task executors

with Hadoop integration

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

Consistency level configurable: ALL, QUORUM, ANY

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

yes

Relationships in Graphs

Transaction concepts

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

ACID

configurable

ACID within a storage node (=shard)

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

off heap cache

User concepts

Access control

yes

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

Role-based access control

Access rights for users and roles

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