DBMS > EsgynDB vs. H2 vs. OrigoDB vs. Pinecone vs. TerarkDB

System Properties Comparison EsgynDB vs. H2 vs. OrigoDB vs. Pinecone vs. TerarkDB

Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

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

A fully ACID in-memory object graph database

A managed, cloud-native vector database

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Relational DBMS

Document store
Object oriented DBMS

Vector DBMS

Key-value store

Secondary database models

Spatial DBMS

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

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	3.16
Rank	#95	Overall
	#2	Vector DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

github.com/bytedance/terarkdb

Technical documentation

www.h2database.com/html/main.html

origodb.com/docs

docs.pinecone.io/docs/overview

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Esgyn

Thomas Mueller

Robert Friberg et al

Pinecone Systems, Inc

ByteDance, originally Terark

Initial release

2015

2005

2009

under the name LiveDB

2019

2016

Current release

2.2.220, July 2023

License

Commercial or Open Source

commercial

Open Source

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

Open Source

commercial

restricted open source version available

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

C++, Java

Java

C++

Server operating systems

Linux

All OS with a Java VM

Linux
Windows

hosted

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

JDBC
ODBC

.NET Client API
HTTP API
LINQ

RESTful HTTP API

C++ API
Java API

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

Java

.Net

Python

C++
Java

Server-side scripts

Stored procedures

Java Stored Procedures

Java Stored Procedures and User-Defined Functions

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

client side managed; servers are not synchronized

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

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

Source-replica replication

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

depending on model

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

Write ahead log

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

Role based authorization

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More resources

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2 June 2023, Matthias Gelbmann

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