DBMS > Apache Pinot vs. HEAVY.AI vs. Lovefield vs. Oracle Rdb

System Properties Comparison Apache Pinot vs. HEAVY.AI vs. Lovefield vs. Oracle Rdb

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Editorial information provided by DB-Engines

Name

Description

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

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Embeddable relational database for web apps written in pure JavaScript

Primary database model

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.58
Rank	#244	Overall
	#111	Relational DBMS

Score	2.10
Rank	#126	Overall
	#61	Relational DBMS

Score	0.32
Rank	#290	Overall
	#132	Relational DBMS

Score	1.08
Rank	#187	Overall
	#85	Relational DBMS

Website

pinot.apache.org

github.com/heavyai/heavydb
www.heavy.ai

google.github.io/lovefield

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

Technical documentation

docs.pinot.apache.org

docs.heavy.ai

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

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

Developer

Apache Software Foundation and contributors

HEAVY.AI, Inc.

Google

Oracle, originally developed by Digital Equipment Corporation (DEC)

Initial release

2015

2016

2014

1984

Current release

1.0.0, September 2023

5.10, January 2022

2.1.12, February 2017

7.4.1.1, 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache 2.0

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++ and CUDA

JavaScript

Server operating systems

All OS with a Java JDK11 or higher

Linux

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

tested with Chrome, Firefox, IE, Safari

HP Open VMS

Data scheme

yes

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

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

SQL

Support of SQL

SQL-like query language

yes

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

JDBC

JDBC
ODBC
Thrift
Vega

Supported programming languages

Go
Java
Python

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript

Server-side scripts

Stored procedures

Triggers

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Round robin

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes, on a single node

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

yes

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

fine grained access rights according to SQL-standard

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More resources

Recent citations in the news

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2 November 2023, Uber

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16 August 2023, InfoQ.com

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20 June 2023, Datanami

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22 March 2022, TechTarget

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3 August 2021, Phoronix

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