DBMS > Amazon DynamoDB vs. Apache Doris vs. Heroic vs. Kinetica vs. Percona Server for MongoDB

System Properties Comparison Amazon DynamoDB vs. Apache Doris vs. Heroic vs. Kinetica vs. Percona Server for MongoDB

Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

An MPP-based analytics DBMS embracing the MySQL protocol

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

Fully vectorized database across both GPUs and CPUs

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

Primary database model

Document store
Key-value store

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.57
Rank	#244	Overall
	#113	Relational DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	0.52
Rank	#254	Overall
	#39	Document stores

Website

aws.amazon.com/dynamodb

doris.apache.org
github.com/apache/doris

github.com/spotify/heroic

www.kinetica.com

www.percona.com/mongodb/software/percona-server-for-mongodb

Technical documentation

docs.aws.amazon.com/dynamodb

github.com/apache/doris/wiki

spotify.github.io/heroic

docs.kinetica.com

docs.percona.com/percona-distribution-for-mongodb

Developer

Amazon

Apache Software Foundation, originally contributed from Baidu

Spotify

Kinetica

Percona

Initial release

2012

2017

2014

2012

2015

Current release

1.2.2, February 2023

7.1, August 2021

3.4.10-2.10, November 2017

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

Open Source

GPL Version 2

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, C++

C++

Server operating systems

hosted

Linux

Data scheme

schema-free

yes

schema-free

yes

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

yes

via Elasticsearch

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

APIs and other access methods

RESTful HTTP API

JDBC
MySQL client

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

JDBC
ODBC
RESTful HTTP API

proprietary protocol using JSON

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Java

C++
Java
JavaScript (Node.js)
Python

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

Server-side scripts

Stored procedures

user defined functions

JavaScript

Triggers

yes

by integration with AWS Lambda

yes

triggers when inserted values for one or more columns fall within a specified range

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

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

GPU vRAM or System RAM

yes

via In-Memory Engine

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

Access rights for users and roles on table level

Access rights for users and roles

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.