DBMS > Ehcache vs. FeatureBase vs. H2GIS vs. HEAVY.AI

System Properties Comparison Ehcache vs. FeatureBase vs. H2GIS vs. HEAVY.AI

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Editorial information provided by DB-Engines

Name

Description

A widely adopted Java cache with tiered storage options

Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.

Spatial extension of H2

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Primary database model

Secondary database models

Relational DBMS

Spatial DBMS

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

Score	4.89
Rank	#67	Overall
	#8	Key-value stores

Score	0.22
Rank	#309	Overall
	#139	Relational DBMS

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Website

www.ehcache.org

www.featurebase.com

www.h2gis.org

github.com/heavyai/heavydb
www.heavy.ai

Technical documentation

www.ehcache.org/documentation

docs.featurebase.com

www.h2gis.org/docs/home

docs.heavy.ai

Developer

Terracotta Inc, owned by Software AG

Molecula and Pilosa Open Source Contributors

CNRS

HEAVY.AI, Inc.

Initial release

2009

2017

2013

2016

Current release

3.10.0, March 2022

2022, May 2022

5.10, January 2022

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

commercial

Open Source

LGPL 3.0

Open Source

Apache Version 2; enterprise edition available

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++ and CUDA

Server operating systems

All OS with a Java VM

Linux
macOS

Linux

Data scheme

schema-free

yes

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

SQL

Support of SQL

SQL queries

yes

APIs and other access methods

JCache

gRPC
JDBC
Kafka Connector
ODBC

JDBC
ODBC
Thrift
Vega

Supported programming languages

Java

Java
Python

Java

All languages supporting JDBC/ODBC/Thrift
Python

Server-side scripts

Stored procedures

yes

based on H2

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

Sharding

none

Sharding

Round robin

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

yes

based on H2

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable Consistency (Strong, Eventual, Weak)

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

supports JTA and can work as an XA resource

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes, using Linux fsync

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

yes

based on H2

fine grained access rights according to SQL-standard

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More resources

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