DBMS > Amazon Aurora vs. FileMaker vs. HarperDB vs. KairosDB vs. Snowflake

System Properties Comparison Amazon Aurora vs. FileMaker vs. HarperDB vs. KairosDB vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

MySQL and PostgreSQL compatible cloud service by Amazon

FileMaker is a cross-platform RDBMS that includes a GUI frontend.

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

Distributed Time Series DBMS based on Cassandra or H2

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Secondary database models

Document store

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

Score	7.57
Rank	#51	Overall
	#32	Relational DBMS

Score	47.91
Rank	#20	Overall
	#14	Relational DBMS

Score	0.60
Rank	#244	Overall
	#38	Document stores

Score	0.67
Rank	#233	Overall
	#20	Time Series DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

aws.amazon.com/rds/aurora

www.claris.com/filemaker

www.harperdb.io

github.com/kairosdb/kairosdb

www.snowflake.com

Technical documentation

docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_Aurora.html

www.claris.com/resources/documentation

docs.harperdb.io/docs

kairosdb.github.io

docs.snowflake.net/manuals/index.html

Developer

Amazon

Claris

a subsidiary of Apple

HarperDB

Snowflake Computing Inc.

Initial release

2015

1983

2017

2013

2014

Current release

19.4.1, November 2021

3.1, August 2021

1.2.2, November 2018

License

Commercial or Open Source

commercial

free community edition available

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

Node.js

Java

Server operating systems

hosted

iOS

client part only
Linux
OS X
Windows

Linux
OS X

Linux
OS X
Windows

hosted

Data scheme

yes

dynamic schema

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

JSON data types

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.

yes

A http query request can return the data in XML format

yes

Secondary indexes

yes

SQL

Support of SQL

yes

via plugins

SQL-like data manipulation statements

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

Filemaker WebDirect
JDBC
ODBC

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

Graphite protocol
HTTP REST
Telnet API

CLI Client
JDBC
ODBC

Supported programming languages

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

PHP

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

Java
JavaScript

Node.js
PHP
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Custom Functions

since release 3.1

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

A table resides as a whole on one (or more) nodes in a cluster

Sharding

based on Cassandra

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Source-replica replication, warm standby

since Version 14

yes

the nodes on which a table resides can be defined

selectable replication factor

based on Cassandra

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using LMDB

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

fine grained access rights according to SQL-standard

simple rights management via user accounts and connection to external directory services

Access rights for users and roles

simple password-based access control

Users with fine-grained authorization concept, user roles and pluggable authentication

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