DBMS > FileMaker vs. RavenDB vs. RRDtool vs. SAP HANA vs. Spark SQL

System Properties Comparison FileMaker vs. RavenDB vs. RRDtool vs. SAP HANA vs. Spark SQL

Editorial information provided by DB-Engines

Name

Description

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

Open Source Operational and Transactional Enterprise NoSQL Document Database

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

In-memory, column based data store. Available as appliance or cloud service

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	48.20
Rank	#20	Overall
	#14	Relational DBMS

Score	2.92
Rank	#101	Overall
	#18	Document stores

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Website

www.claris.com/filemaker

ravendb.net

oss.oetiker.ch/rrdtool

www.sap.com/products/hana.html

spark.apache.org/sql

Technical documentation

www.claris.com/resources/documentation

ravendb.net/docs

oss.oetiker.ch/rrdtool/doc

help.sap.com/hana

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Claris

a subsidiary of Apple

Hibernating Rhinos

Tobias Oetiker

SAP

Apache Software Foundation

Initial release

1983

2010

1999

2010

2014

Current release

19.4.1, November 2021

5.4, July 2022

1.8.0, 2022

2.0 SPS07 (April 4, 2023), April 2023

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

Open Source

AGPL version 3, commercial license available

Open Source

GPL V2 and FLOSS

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Implementations in Java (e.g. RRD4J) and C# available

Scala

Server operating systems

iOS

client part only
Linux
OS X
Windows

Linux
macOS
Raspberry Pi
Windows

HP-UX
Linux

Appliance or cloud-service

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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

Exporting into and restoring from XML files possible

Secondary indexes

yes

SQL

Support of SQL

yes

via plugins

SQL-like query language (RQL)

yes

SQL-like DML and DDL statements

APIs and other access methods

Filemaker WebDirect
JDBC
ODBC

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

in-process shared library
Pipes

JDBC
ODBC

Supported programming languages

PHP

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

Java
Python
R
Scala

Server-side scripts

Stored procedures

yes

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

yes

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication, warm standby

since Version 14

Multi-source replication

none

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID, Cluster-wide transaction available

ACID

Concurrency

Support for concurrent manipulation of data

yes

by using the rrdcached daemon

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

Authorization levels configured per client per database

yes

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