DBMS > Apache IoTDB vs. Badger vs. Drizzle vs. Oracle NoSQL

System Properties Comparison Apache IoTDB vs. Badger vs. Drizzle vs. Oracle NoSQL

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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

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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

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

Key-value store

Relational DBMS

Document store
Key-value store
Relational DBMS

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

Score	1.31
Rank	#159	Overall
	#14	Time Series DBMS

Score	0.14
Rank	#328	Overall
	#48	Key-value stores

Score	3.07
Rank	#86	Overall
	#15	Document stores
	#11	Key-value stores
	#47	Relational DBMS

Website

iotdb.apache.org

github.com/dgraph-io/badger

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

Technical documentation

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

godoc.org/github.com/dgraph-io/badger

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

Developer

Apache Software Foundation

DGraph Labs

Drizzle project, originally started by Brian Aker

Oracle

Initial release

2018

2017

2008

2011

Current release

1.1.0, April 2023

7.2.4, September 2012

24.1, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

GNU GPL

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

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)

BSD
Linux
OS X
Solaris
Windows

FreeBSD
Linux
OS X

Linux
Solaris SPARC/x86

Data scheme

yes

schema-free

yes

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

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

SQL-like DML and DDL statements

APIs and other access methods

JDBC
Native API

JDBC

RESTful HTTP API

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

C
C++
Java
PHP

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

Server-side scripts

Stored procedures

yes

Triggers

yes

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

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

none

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

none

Multi-source replication
Source-replica replication

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

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

none

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

yes

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights for users and roles

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