DBMS > atoti vs. Ehcache vs. GeoMesa vs. Heroic vs. Kyligence Enterprise

System Properties Comparison atoti vs. Ehcache vs. GeoMesa vs. Heroic vs. Kyligence Enterprise

Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

A widely adopted Java cache with tiered storage options

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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

A distributed analytics engine for big data, built on top of Apache Kylin

Primary database model

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

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

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

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	0.40
Rank	#269	Overall
	#124	Relational DBMS

Website

atoti.io

www.ehcache.org

www.geomesa.org

github.com/spotify/heroic

kyligence.io/kyligence-enterprise

Technical documentation

docs.atoti.io

www.ehcache.org/documentation

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

spotify.github.io/heroic

Developer

ActiveViam

Terracotta Inc, owned by Software AG

CCRi and others

Spotify

Kyligence, Inc.

Initial release

2009

2014

2016

Current release

3.10.0, March 2022

4.0.5, February 2024

License

Commercial or Open Source

commercial

free versions available

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache License 2.0

Open Source

Apache 2.0

commercial

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

Scala

Java

Server operating systems

All OS with a Java VM

Linux

Data scheme

schema-free

yes

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

via Elasticsearch

yes

SQL

Support of SQL

Multidimensional Expressions (MDX)

ANSI SQL for queries (using Apache Calcite)

APIs and other access methods

JCache

HQL (Heroic Query Language, a JSON-based language)
HTTP API

JDBC
ODBC
RESTful HTTP API

Supported programming languages

Java

Server-side scripts

Stored procedures

Python

Triggers

yes

Cache Event Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

by using Terracotta Server

depending on storage layer

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

depending on storage layer

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable Consistency (Strong, Eventual, Weak)

depending on storage layer

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

supports JTA and can work as an XA resource

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes

In-memory capabilities

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

yes

depending on storage layer

User concepts

Access control

yes

depending on the DBMS used for storage

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More resources

DB-Engines blog posts

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