DBMS > Apache Pinot vs. FatDB vs. Hypertable vs. YDB

System Properties Comparison Apache Pinot vs. FatDB vs. Hypertable vs. YDB

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Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

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

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

An open source BigTable implementation based on distributed file systems such as Hadoop

A distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API

Primary database model

Relational DBMS

Document store
Key-value store

Wide column store

Document 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	0.39
Rank	#269	Overall
	#43	Document stores
	#126	Relational DBMS

Website

pinot.apache.org

github.com/ydb-platform/ydb
ydb.tech

Technical documentation

docs.pinot.apache.org

ydb.tech/en/docs

Developer

Apache Software Foundation and contributors

FatCloud

Hypertable Inc.

Yandex

Initial release

2015

2012

2009

2019

Current release

1.0.0, September 2023

0.9.8.11, March 2016

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

GNU version 3. Commercial license available

Open Source

Apache 2.0; commercial license available

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

Windows

Linux
OS X
Windows

an inofficial Windows port is available

Linux

Data scheme

yes

schema-free

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

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

SQL-like query language

Via inetgration in SQL Server

SQL-like query language (YQL)

APIs and other access methods

JDBC

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

C++ API
Thrift

RESTful HTTP API (DynamoDB compatible)

Supported programming languages

Go
Java
Python

C++
Java
Perl
PHP
Python
Ruby

Go
Java
JavaScript (Node.js)
PHP
Python

Server-side scripts

Stored procedures

yes

via applications

Triggers

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

selectable replication factor on file system level

Active-passive shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

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.

User concepts

Access control

Can implement custom security layer via applications

Access rights defined for Yandex Cloud users

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