DBMS > GridDB vs. MySQL vs. ObjectBox vs. SAP HANA

System Properties Comparison GridDB vs. MySQL vs. ObjectBox vs. SAP HANA

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Editorial information provided by DB-Engines

Name

Description

Scalable in-memory time series database optimized for IoT and Big Data

Widely used open source RDBMS

Lightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectors

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

Object oriented DBMS
Vector DBMS

Relational DBMS

Secondary database models

Key-value store
Relational DBMS

Document store
Spatial DBMS

Time Series DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	1.91
Rank	#123	Overall
	#10	Time Series DBMS

Score	1029.49
Rank	#2	Overall
	#2	Relational DBMS

Score	1.08
Rank	#179	Overall
	#6	Object oriented DBMS
	#9	Vector DBMS

Score	41.32
Rank	#23	Overall
	#16	Relational DBMS

Website

griddb.net

www.mysql.com

github.com/objectbox
objectbox.io

www.sap.com/products/hana.html

Technical documentation

Developer

Toshiba Corporation

Oracle

since 2010, originally MySQL AB, then Sun

ObjectBox Limited

SAP

Initial release

2013

1995

2017

2010

Current release

5.1, August 2022

9.0.0, July 2024

4.0 (May 2024)

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Bindings are released under Apache 2.0

Apache License 2.0

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

C and C++

Server operating systems

Linux

FreeBSD
Linux
OS X
Solaris
Windows

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

Appliance or cloud-service

Data scheme

yes

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

yes

yes, plus "flex" map-like 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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL92, SQL-like TQL (Toshiba Query Language)

yes

with proprietary extensions

yes

APIs and other access methods

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
Proprietary native API

Proprietary native API

JDBC
ODBC

Supported programming languages

C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

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 (Flutter)
Go
Java
Kotlin
Python
Swift

Server-side scripts

Stored procedures

yes

proprietary syntax

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

Data sync between devices allowing occasional connected databases to work completely offline

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency within container, eventual consistency across containers

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

ACID at container level

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

Access rights for users can be defined per database

Users with fine-grained authorization concept

no user groups or roles

yes

More information provided by the system vendor

News

MongoDB Realm & Device Sync alternatives – ObjectBox
17 September 2024

Local AI – what it is and why we need it
11 September 2024

First on-device Vector Database (aka Semantic Index) for iOS
24 July 2024

Retrieval Augmented Generation (RAG) with vector databases: Expanding AI Capabilities
18 June 2024

The on-device Vector Database for Android and Java
29 May 2024

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