DBMS > Amazon DocumentDB vs. chDB vs. Hawkular Metrics vs. ITTIA

System Properties Comparison Amazon DocumentDB vs. chDB vs. Hawkular Metrics vs. ITTIA

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Editorial information provided by DB-Engines

Name

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

An embedded SQL OLAP Engine powered by ClickHouse

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

Edge Time Series DBMS with Real-Time Stream Processing

Primary database model

Document store

Relational DBMS

Time Series DBMS

Secondary database models

Time Series DBMS

Relational DBMS

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

Score	1.91
Rank	#131	Overall
	#24	Document stores

Score	0.07
Rank	#376	Overall
	#158	Relational DBMS

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	0.44
Rank	#267	Overall
	#23	Time Series DBMS

Website

aws.amazon.com/documentdb

github.com/chdb-io/chdb

www.hawkular.org

www.ittia.com

Technical documentation

aws.amazon.com/documentdb/resources

doc.chdb.io

www.hawkular.org/hawkular-metrics/docs/user-guide

Developer

Community supported by Red Hat

ITTIA L.L.C.

Initial release

2019

2023

2014

2007

Current release

8.7

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache 2.0

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

Java

C and C++

Server operating systems

hosted

server-less

Linux
OS X
Windows

Linux
Windows

Data scheme

schema-free

Fixed schema

Typing

predefined data types such as float or date

yes

Float/Blob/Integer/String/Unicode/Date/Time/Timestamp/Interval

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

Close to ANSI SQL (SQL/JSON + extensions)

yes

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

HTTP REST

JDBC
ODBC
RESTful HTTP API
WebSocket

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

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

Go
Java
Python
Ruby

C
C++
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

selectable replication factor

based on Cassandra

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

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

Atomic single-document operations

yes

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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.

yes

User concepts

Access control

Access rights for users and roles

Database file passwords

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More resources

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