DBMS > Apache IoTDB vs. Blazegraph vs. etcd vs. JanusGraph vs. RocksDB

System Properties Comparison Apache IoTDB vs. Blazegraph vs. etcd vs. JanusGraph vs. RocksDB

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 distributed reliable key-value store

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

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	7.03
Rank	#54	Overall
	#5	Key-value stores

Score	2.02
Rank	#125	Overall
	#12	Graph DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

iotdb.apache.org

blazegraph.com

etcd.io
github.com/etcd-io/etcd

janusgraph.org

rocksdb.org

Technical documentation

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

wiki.blazegraph.com

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

docs.janusgraph.org

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation

Blazegraph

Linux Foundation; originally developed as Titan by Aurelius

Facebook, Inc.

Initial release

2018

2006

2017

2013

Current release

1.1.0, April 2023

2.1.5, March 2019

3.4, August 2019

0.6.3, February 2023

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

extended commercial license available

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

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Implementation language

Java

C++

Server operating systems

All OS with a Java VM (>= 1.8)

Linux
OS X
Windows

FreeBSD
Linux
Windows

experimental

Linux
OS X
Unix
Windows

Linux

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

RDF literal types

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.

Secondary indexes

yes

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

gRPC
JSON over HTTP

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

C++ API
Java API

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

Clojure
Java
Python

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

yes, watching key changes

yes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

horizontal partitioning

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

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

yes

via Faunus, a graph analytics engine

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

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in Graphs

yes

Relationships in graphs

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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)

User authentification and security via Rexster Graph Server

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