DBMS > Apache Pinot vs. BigObject vs. Cachelot.io

System Properties Comparison Apache Pinot vs. BigObject vs. Cachelot.io

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Editorial information provided by DB-Engines

Name

Description

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

Analytic DBMS for real-time computations and queries

In-memory caching system

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Key-value store

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Trend Chart

Score	0.58
Rank	#244	Overall
	#111	Relational DBMS

Score	0.13
Rank	#342	Overall
	#150	Relational DBMS

Score	0.00
Rank	#396	Overall
	#64	Key-value stores

Website

pinot.apache.org

bigobject.io

cachelot.io

Technical documentation

docs.pinot.apache.org

docs.bigobject.io

Developer

Apache Software Foundation and contributors

BigObject, Inc.

Initial release

2015

Current release

1.0.0, September 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free community edition available

Open Source

Simplified BSD License

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++

Server operating systems

All OS with a Java JDK11 or higher

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

FreeBSD
Linux
OS X

Data scheme

yes

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

SQL-like DML and DDL statements

APIs and other access methods

JDBC

fluentd
ODBC
RESTful HTTP API

Memcached protocol

Supported programming languages

Go
Java
Python

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

Lua

Triggers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

Transaction concepts

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

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

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More resources

Recent citations in the news

Real-Time Analytics for Mobile App Crashes using Apache Pinot
2 November 2023, Uber

Speed of Apache Pinot at the Cost of Cloud Object Storage with Tiered Storage
16 August 2023, InfoQ.com

StarTree Announces Integration between Apache Pinot and Delta Lake with StarTree Cloud
20 June 2023, Datanami

StarTree brings Apache Pinot real-time database to the cloud
22 March 2022, TechTarget

Data analytics startup StarTree secures cash to expand its Apache Pinot-powered platform
29 August 2022, TechCrunch

provided by Google News

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