DBMS > Apache Doris vs. H2 vs. Hypertable vs. Pinecone

System Properties Comparison Apache Doris vs. H2 vs. Hypertable vs. Pinecone

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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

An MPP-based analytics DBMS embracing the MySQL protocol

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

A managed, cloud-native vector database

Primary database model

Relational DBMS

Wide column store

Vector DBMS

Secondary database models

Spatial DBMS

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

Score	0.61
Rank	#235	Overall
	#110	Relational DBMS

Score	7.57
Rank	#47	Overall
	#30	Relational DBMS

Score	3.02
Rank	#87	Overall
	#3	Vector DBMS

Website

doris.apache.org
github.com/apache/doris

www.h2database.com

www.pinecone.io

Technical documentation

github.com/apache/doris/wiki

www.h2database.com/html/main.html

docs.pinecone.io/docs/overview

Developer

Apache Software Foundation, originally contributed from Baidu

Thomas Mueller

Hypertable Inc.

Pinecone Systems, Inc

Initial release

2017

2005

2009

2019

Current release

1.2.2, February 2023

2.2.220, July 2023

0.9.8.11, March 2016

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

commercial

Cloud-based only

Only available as a cloud service

yes

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

Linux

All OS with a Java VM

Linux
OS X
Windows

an inofficial Windows port is available

hosted

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

String, Number, Boolean

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

yes

APIs and other access methods

JDBC
MySQL client

JDBC
ODBC

C++ API
Thrift

RESTful HTTP API

Supported programming languages

Java

C++
Java
Perl
PHP
Python
Ruby

Python

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures and User-Defined Functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

selectable replication factor on file system level

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

yes, multi-version concurrency control (MVCC)

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

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

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2 June 2023, Matthias Gelbmann

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