DBMS > Apache Pinot vs. GridDB vs. OpenEdge vs. Oracle NoSQL vs. Oracle Rdb

System Properties Comparison Apache Pinot vs. GridDB vs. OpenEdge vs. Oracle NoSQL vs. Oracle Rdb

Editorial information provided by DB-Engines

Name

Description

Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency

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

Application development environment with integrated database management system

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

Relational DBMS

Time Series DBMS

Relational DBMS

Document store
Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Key-value store
Relational DBMS

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

Score	0.35
Rank	#274	Overall
	#128	Relational DBMS

Score	1.91
Rank	#123	Overall
	#10	Time Series DBMS

Score	3.69
Rank	#78	Overall
	#42	Relational DBMS

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

Score	1.04
Rank	#184	Overall
	#84	Relational DBMS

Website

pinot.apache.org

griddb.net

www.progress.com/openedge

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

www.oracle.com/database/technologies/related/rdb.html

Technical documentation

docs.pinot.apache.org

docs.griddb.net

documentation.progress.com/output/ua/OpenEdge_latest

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

www.oracle.com/database/technologies/related/rdb-doc.html

Developer

Apache Software Foundation and contributors

Toshiba Corporation

Progress Software Corporation

Oracle

Oracle, originally developed by Digital Equipment Corporation (DEC)

Initial release

2015

2013

1984

2011

1984

Current release

1.0.0, September 2023

5.1, August 2022

OpenEdge 12.2, March 2020

24.1, May 2024

7.4.1.1, 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

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

commercial

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

commercial

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 JDK11 or higher

Linux

AIX
HP-UX
Linux
Solaris
Windows

Linux
Solaris SPARC/x86

HP Open VMS

Data scheme

yes

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

Flexible Schema (defined schema, partial schema, schema free)

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

yes

optional

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

SQL-like query language

SQL92, SQL-like TQL (Toshiba Query Language)

yes

close to SQL 92

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

JDBC
ODBC

RESTful HTTP API

Supported programming languages

Go
Java
Python

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

Progress proprietary ABL (Advanced Business Language)

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

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

horizontal partitioning

since Version 11.4

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

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

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency within container, eventual consistency across containers

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID at container level

ACID

configurable

ACID within a storage node (=shard)

yes, on a single node

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

Access rights for users can be defined per database

Users and groups

Access rights for users and roles

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Build a real-time analytics solution with Apache Pinot on AWS
6 August 2024, AWS Blog

Open source Apache Pinot advances as StarTree boosts real-time analytics and observability
8 May 2024, VentureBeat

StarTree broadly enhances Apache Pinot-based analytics platform
8 May 2024, SiliconANGLE News

Pinot for Low-Latency Offline Table Analytics
29 August 2024, Uber

StarTree Finds Apache Pinot the Right Vintage for IT Observability
8 May 2024, Datanami

provided by Google News

Now Features Scale-Out and Scale-Up combo for Petabyte-scale Data Management
3 December 2019, global.toshiba

’s SQL Interface, Aims to Accelerate Open Innovation
17 June 2020, global.toshiba

TOSHIBA DIGITAL SOLUTIONS CORPORATION
1 November 2020, global.toshiba

IoT: Opt for the Right Open Source Database
11 August 2023, Open Source For You

Toshiba Digital Solutions collaborates with DATAFLUCT to Deliver a Machine Learning Solution that Optimizes Store Visitors Prediction ~ The integration of Cloud Data Infrastructure and Auto Machine Learning enables accurate prediction without experts inter
21 April 2021, global.toshiba

provided by Google News

What's New in OpenEdge 12.8
15 April 2024, release.nl

4 sources of latency and how to avoid them
1 November 2017, InfoWorld

provided by Google News

Cloud database comparison: AWS, Microsoft, Google and Oracle
24 July 2024, TechTarget

Top 8 Best NoSQL Databases in 2024
9 September 2024, AIM

Oracle GoldenGate for Big Data Articles get a new look!
30 October 2023, Oracle

Oracle, Uni. Of Mauritius develop breast cancer awareness app
13 August 2024, Africanews English

Explore Oracle Database Solutions for Maximum Efficiency
4 September 2018, oracle.com

provided by Google News

Oracle Adds New AI-Enabling Features To MySQL HeatWave
23 March 2023, Forbes

Oracle Business Model
13 June 2023, Business Model Analyst

provided by Google News

Share this page