DBMS > atoti vs. chDB vs. Ehcache

System Properties Comparison atoti vs. chDB vs. Ehcache

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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.

An embedded SQL OLAP Engine powered by ClickHouse

A widely adopted Java cache with tiered storage options

Primary database model

Object oriented DBMS

Relational DBMS

Key-value store

Secondary database models

Time Series DBMS

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

Score	0.61
Rank	#243	Overall
	#10	Object oriented DBMS

Score	0.07
Rank	#376	Overall
	#158	Relational DBMS

Score	4.64
Rank	#68	Overall
	#8	Key-value stores

Website

atoti.io

github.com/chdb-io/chdb

www.ehcache.org

Technical documentation

docs.atoti.io

doc.chdb.io

www.ehcache.org/documentation

Developer

ActiveViam

Terracotta Inc, owned by Software AG

Initial release

2023

2009

Current release

3.10.0, March 2022

License

Commercial or Open Source

commercial

free versions available

Open Source

Apache Version 2.0

Open Source

Apache Version 2; commercial licenses 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

Server operating systems

server-less

All OS with a Java VM

Data scheme

schema-free

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

SQL

Support of SQL

Multidimensional Expressions (MDX)

Close to ANSI SQL (SQL/JSON + extensions)

APIs and other access methods

JCache

Supported programming languages

Bun
C
C++
Go
JavaScript (Node.js)
Python
Rust

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

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)

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

In-memory capabilities

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

yes

User concepts

Access control

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