DBMS > GeoMesa vs. H2 vs. HyperSQL vs. Pinecone vs. Snowflake

System Properties Comparison GeoMesa vs. H2 vs. HyperSQL vs. Pinecone vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

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

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

A managed, cloud-native vector database

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Secondary database models

Spatial DBMS

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

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Score	3.23
Rank	#92	Overall
	#2	Vector DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

Technical documentation

www.geomesa.org/documentation/stable/user/index.html

www.h2database.com/html/main.html

hsqldb.org/web/hsqlDocsFrame.html

docs.pinecone.io/docs/overview

docs.snowflake.net/manuals/index.html

Developer

CCRi and others

Thomas Mueller

Pinecone Systems, Inc

Snowflake Computing Inc.

Initial release

2014

2005

2001

2019

2014

Current release

5.0.0, May 2024

2.2.220, July 2023

2.7.2, June 2023

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

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

Open Source

based on BSD license

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

Scala

Java

Server operating systems

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

hosted

Data scheme

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

String, Number, Boolean

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

JDBC
ODBC

HTTP API

JDBC via HTTP
JDBC
ODBC

RESTful HTTP API

CLI Client
JDBC
ODBC

Supported programming languages

Java

All languages supporting JDBC/ODBC
Java

Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

Java, SQL

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

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

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

depending on storage layer

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.

depending on storage layer

yes

User concepts

Access control

yes

depending on the DBMS used for storage

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles and pluggable authentication

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