DBMS > Apache Pinot vs. H2 vs. Hypertable vs. LevelDB

System Properties Comparison Apache Pinot vs. H2 vs. Hypertable vs. LevelDB

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Editorial information provided by DB-Engines

Name

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

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

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

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Primary database model

Relational DBMS

Wide column store

Key-value store

Secondary database models

Spatial DBMS

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

Score	0.35
Rank	#274	Overall
	#128	Relational DBMS

Score	7.57
Rank	#47	Overall
	#30	Relational DBMS

Score	2.33
Rank	#111	Overall
	#19	Key-value stores

Website

pinot.apache.org

www.h2database.com

github.com/google/leveldb

Technical documentation

docs.pinot.apache.org

www.h2database.com/html/main.html

github.com/google/leveldb/blob/main/doc/index.md

Developer

Apache Software Foundation and contributors

Thomas Mueller

Hypertable Inc.

Google

Initial release

2015

2005

2009

2011

Current release

1.0.0, September 2023

2.2.220, July 2023

0.9.8.11, March 2016

1.23, February 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

GNU version 3. Commercial license available

Open Source

BSD

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++

Server operating systems

All OS with a Java JDK11 or higher

All OS with a Java VM

Linux
OS X
Windows

an inofficial Windows port is available

Illumos
Linux
OS X
Windows

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

restricted

only exact value or prefix value scans

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

JDBC

JDBC
ODBC

C++ API
Thrift

Supported programming languages

Go
Java
Python

Java

C++
Java
Perl
PHP
Python
Ruby

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

With clustering: 2 database servers on different computers operate on identical copies of a database

selectable replication factor on file system level

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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