DBMS > FileMaker vs. Newts vs. Snowflake vs. Solr vs. Teradata

System Properties Comparison FileMaker vs. Newts vs. Snowflake vs. Solr vs. Teradata

Editorial information provided by DB-Engines

Name

Description

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

Time Series DBMS based on Cassandra

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

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

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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Trend Chart

Score	48.20
Rank	#20	Overall
	#14	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	42.91
Rank	#24	Overall
	#3	Search engines

Score	45.33
Rank	#21	Overall
	#15	Relational DBMS

Website

www.claris.com/filemaker

opennms.github.io/newts

www.snowflake.com

solr.apache.org

www.teradata.com

Technical documentation

www.claris.com/resources/documentation

github.com/OpenNMS/newts/wiki

docs.snowflake.net/manuals/index.html

solr.apache.org/resources.html

docs.teradata.com

Developer

Claris

a subsidiary of Apple

OpenNMS Group

Snowflake Computing Inc.

Apache Software Foundation

Teradata

Initial release

1983

2014

2006

1984

Current release

19.4.1, November 2021

9.6.0, April 2024

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

Apache Version 2

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

Java

Server operating systems

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)

hosted
Linux

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

yes

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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

All search fields are automatically indexed

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

yes

via plugins

yes

Solr Parallel SQL Interface

yes

SQL 2016 + extensions

APIs and other access methods

Filemaker WebDirect
JDBC
ODBC

HTTP REST
Java API

CLI Client
JDBC
ODBC

Java API
RESTful HTTP/JSON API

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

PHP

Java

JavaScript (Node.js)
Python

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

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

yes

user defined functions

Java plugins

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

similar concept for controling cloud resources

yes

User configurable commands triggered on index changes

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

yes

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication, warm standby

since Version 14

selectable replication factor

based on Cassandra

yes

Multi-source replication
Source-replica replication

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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

optimistic locking

ACID

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

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

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

yes

fine grained access rights according to SQL-standard

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