DBMS > Apache Druid vs. HBase vs. MySQL vs. ObjectBox vs. Teradata

System Properties Comparison Apache Druid vs. HBase vs. MySQL vs. ObjectBox vs. Teradata

Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

Wide-column store based on Apache Hadoop and on concepts of BigTable

Widely used open source RDBMS

Extremely fast embedded database for small devices, IoT and Mobile

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Relational DBMS
Time Series DBMS

Wide column store

Relational DBMS

Key/Value like access via memcached API

Object oriented DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Time Series DBMS

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	1.20
Rank	#170	Overall
	#5	Object oriented DBMS

Score	45.33
Rank	#21	Overall
	#15	Relational DBMS

Website

Technical documentation

druid.apache.org/docs/latest/design

hbase.apache.org/book.html

dev.mysql.com/doc

docs.objectbox.io

docs.teradata.com

Developer

Apache Software Foundation and contributors

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Oracle

since 2010, originally MySQL AB, then Sun

ObjectBox Limited

Teradata

Initial release

2012

2008

1995

2017

1984

Current release

29.0.1, April 2024

2.3.4, January 2021

8.4.0, April 2024

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache version 2

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache License 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C and C++

Server operating systems

Linux
OS X
Unix

Linux
Unix
Windows

using Cygwin

FreeBSD
Linux
OS X
Solaris
Windows

Android
iOS
Linux
macOS
Windows

hosted
Linux

Data scheme

yes

schema-less columns are supported

schema-free, schema definition possible

yes

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

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.

yes

Secondary indexes

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

SQL for querying

yes

with proprietary extensions

yes

SQL 2016 + extensions

APIs and other access methods

JDBC
RESTful HTTP/JSON API

Java API
RESTful HTTP API
Thrift

ADO.NET
JDBC
ODBC
Proprietary native API

Proprietary native API

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C
C#
C++
Groovy
Java
PHP
Python
Scala

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

yes

Coprocessors in Java

yes

proprietary syntax

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Multi-source replication
Source-replica replication

online/offline synchronization between client and server

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

Single row ACID (across millions of columns)

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

Users with fine-grained authorization concept

no user groups or roles

yes

fine grained access rights according to SQL-standard

More information provided by the system vendor

News

On-device Vector Database for Dart/Flutter
21 May 2024

The first On-Device Vector Database: ObjectBox 4.0
16 May 2024

Edge AI: The era of on-device AI
23 April 2024

In-Memory Database Use Cases
15 February 2024

Data Viewer for Objects – announcing ObjectBox Admin
14 November 2023

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