DBMS > Amazon DocumentDB vs. Hawkular Metrics vs. openGemini vs. RocksDB

System Properties Comparison Amazon DocumentDB vs. Hawkular Metrics vs. openGemini vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

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

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

An open source distributed Time Series DBMS with high concurrency, high performance, and high scalability

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Document store

Time Series DBMS

Key-value store

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

Score	1.91
Rank	#124	Overall
	#22	Document stores

Score	0.01
Rank	#377	Overall
	#39	Time Series DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	2.84
Rank	#97	Overall
	#16	Key-value stores

Website

aws.amazon.com/documentdb

www.hawkular.org

www.opengemini.org
github.com/openGemini

rocksdb.org

Technical documentation

aws.amazon.com/documentdb/resources

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

docs.opengemini.org/guide

github.com/facebook/rocksdb/wiki

Developer

Community supported by Red Hat

Huawei and openGemini community

Facebook, Inc.

Initial release

2019

2014

2022

2013

Current release

1.1, July 2023

9.4.0, June 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Open Source

BSD

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++

Server operating systems

hosted

Linux
OS X
Windows

Linux
Windows

Linux

Data scheme

schema-free

Typing

predefined data types such as float or date

yes

Integer, Float, Boolean, String

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-like query language

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

HTTP REST

C++ API
Java API

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

Go
Java
Python
Ruby

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

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

Triggers

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

Sharding

horizontal partitioning

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

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

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

Administrators and common users accounts

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