DBMS > Apache IoTDB vs. Cloudflare Workers KV vs. HugeGraph vs. Trafodion

System Properties Comparison Apache IoTDB vs. Cloudflare Workers KV vs. HugeGraph vs. Trafodion

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Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

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

A global, low-latency, key-value store for applications on Cloudflare with exceptionally high read volumes and low-latency.

A fast-speed and highly-scalable Graph DBMS

Transactional SQL-on-Hadoop DBMS

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	0.39
Rank	#274	Overall
	#39	Key-value stores

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Website

iotdb.apache.org

www.cloudflare.com/developer-platform/workers-kv

github.com/hugegraph
hugegraph.apache.org

trafodion.apache.org

Technical documentation

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

developers.cloudflare.com/kv/api

hugegraph.apache.org/docs

trafodion.apache.org/documentation.html

Developer

Apache Software Foundation

Cloudflare

Baidu

Apache Software Foundation, originally developed by HP

Initial release

2018

2014

Current release

1.1.0, April 2023

0.9

2.3.0, February 2019

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++, Java

Server operating systems

All OS with a Java VM (>= 1.8)

hosted

Linux
macOS
Unix

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

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

also supports composite index and range index

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

JDBC
Native API

HTTP REST
Proprietary protocol

Java API
RESTful HTTP API
TinkerPop Gremlin

ADO.NET
JDBC
ODBC

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala

Groovy
Java
Python

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

yes

asynchronous Gremlin script jobs

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

yes

depending on used storage backend, e.g. Cassandra and HBase

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

depending on used storage backend, e.g. Cassandra and HBase

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

via hugegraph-spark

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

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.

yes

User concepts

Access control

yes

Users, roles and permissions

fine grained access rights according to SQL-standard

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