DBMS > Apache IoTDB vs. Drizzle vs. HugeGraph vs. Lovefield

System Properties Comparison Apache IoTDB vs. Drizzle vs. HugeGraph vs. Lovefield

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle 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

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

A fast-speed and highly-scalable Graph DBMS

Embeddable relational database for web apps written in pure JavaScript

Primary database model

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

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Website

iotdb.apache.org

github.com/hugegraph
hugegraph.apache.org

google.github.io/lovefield

Technical documentation

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

hugegraph.apache.org/docs

github.com/google/lovefield/blob/master/docs/spec_index.md

Developer

Apache Software Foundation

Drizzle project, originally started by Brian Aker

Baidu

Google

Initial release

2018

2008

2018

2014

Current release

1.1.0, April 2023

7.2.4, September 2012

0.9

2.1.12, February 2017

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

GNU GPL

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C++

Java

JavaScript

Server operating systems

All OS with a Java VM (>= 1.8)

FreeBSD
Linux
OS X

Linux
macOS
Unix

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Data scheme

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

with proprietary extensions

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

JDBC
Native API

JDBC

Java API
RESTful HTTP API
TinkerPop Gremlin

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

C
C++
Java
PHP

Groovy
Java
Python

JavaScript

Server-side scripts

Stored procedures

yes

asynchronous Gremlin script jobs

Triggers

yes

hooks for callbacks inside the server can be used.

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

yes

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

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

Multi-source replication
Source-replica replication

yes

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

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Eventual 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

yes, by using IndexedDB or the cloud service Firebase Realtime Database

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

User concepts

Access control

yes

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Users, roles and permissions

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More resources

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