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

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

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.

Distributed Time Series DBMS based on Cassandra or H2

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

A widely used distributed, scalable search engine based on Apache Lucene

Primary database model

Secondary database models

Document store

Spatial DBMS

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	0.67
Rank	#233	Overall
	#20	Time Series DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	41.02
Rank	#24	Overall
	#3	Search engines

Website

aws.amazon.com/rds/aurora

www.claris.com/filemaker

github.com/kairosdb/kairosdb

www.snowflake.com

solr.apache.org

Technical documentation

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

www.claris.com/resources/documentation

kairosdb.github.io

docs.snowflake.net/manuals/index.html

solr.apache.org/resources.html

Developer

Amazon

Claris

a subsidiary of Apple

Snowflake Computing Inc.

Apache Software Foundation

Initial release

2015

1983

2013

2014

2006

Current release

19.4.1, November 2021

1.2.2, November 2018

9.6.1, May 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

Apache 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

Server operating systems

hosted

iOS

client part only
Linux
OS X
Windows

Linux
OS X
Windows

hosted

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Data scheme

yes

schema-free

yes

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

yes

Dynamic Fields enables on-the-fly addition of new fields

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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

All search fields are automatically indexed

SQL

Support of SQL

yes

via plugins

yes

Solr Parallel SQL Interface

APIs and other access methods

ADO.NET
JDBC
ODBC

Filemaker WebDirect
JDBC
ODBC

Graphite protocol
HTTP REST
Telnet API

CLI Client
JDBC
ODBC

Java API
RESTful HTTP/JSON API

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

Java
JavaScript

Node.js
PHP
Python

JavaScript (Node.js)
Python

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

user defined functions

Java plugins

Triggers

yes

similar concept for controling cloud resources

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Sharding

based on Cassandra

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Source-replica replication, warm standby

since Version 14

selectable replication factor

based on Cassandra

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

optimistic locking

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

fine grained access rights according to SQL-standard

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

simple password-based access control

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

yes

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