DBMS > Amazon DocumentDB vs. Bangdb vs. Hawkular Metrics vs. PlanetScale

System Properties Comparison Amazon DocumentDB vs. Bangdb vs. Hawkular Metrics vs. PlanetScale

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Editorial information provided by DB-Engines

Name

Description

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

Converged and high performance database for device data, events, time series, document and graph

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

Scalable, distributed, serverless MySQL database platform built on top of Vitess

Primary database model

Document store

Document store
Graph DBMS
Time Series DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

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

Score	1.91
Rank	#124	Overall
	#22	Document stores

Score	0.07
Rank	#346	Overall
	#47	Document stores
	#35	Graph DBMS
	#32	Time Series DBMS

Score	0.01
Rank	#377	Overall
	#39	Time Series DBMS

Score	1.09
Rank	#178	Overall
	#82	Relational DBMS

Website

aws.amazon.com/documentdb

bangdb.com

www.hawkular.org

planetscale.com

Technical documentation

aws.amazon.com/documentdb/resources

docs.bangdb.com

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

planetscale.com/docs

Developer

Sachin Sinha, BangDB

Community supported by Red Hat

PlanetScale

Initial release

2019

2012

2014

2020

Current release

BangDB 2.0, October 2021

License

Commercial or Open Source

commercial

Open Source

BSD 3

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

C, C++

Java

Server operating systems

hosted

Linux

Linux
OS X
Windows

Docker
Linux
macOS

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

yes: string, long, double, int, geospatial, stream, events

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

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

yes

with proprietary extensions

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

Proprietary protocol
RESTful HTTP API

HTTP REST

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

C
C#
C++
Java
Python

Go
Java
Python
Ruby

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

proprietary syntax

Triggers

yes, Notifications (with Streaming only)

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Sharding

based on Cassandra

Sharding

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, Knob for CAP (enterprise version only)

selectable replication factor

based on Cassandra

Multi-source replication
Source-replica replication

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

Tunable consistency, set CAP knob accordingly

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

not for MyISAM storage engine

Transaction concepts

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

Atomic single-document operations

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

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

yes, run db with in-memory only mode

yes

User concepts

Access control

Access rights for users and roles

yes (enterprise version only)

Users with fine-grained authorization concept

no user groups or roles

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