DBMS > FileMaker vs. HEAVY.AI vs. Microsoft Azure Table Storage vs. RocksDB

System Properties Comparison FileMaker vs. HEAVY.AI vs. Microsoft Azure Table Storage vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

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

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

A Wide Column Store for rapid development using massive semi-structured datasets

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Relational DBMS

Wide column store

Key-value store

Secondary database models

Spatial DBMS

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

Score	47.91
Rank	#20	Overall
	#14	Relational DBMS

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

www.claris.com/filemaker

github.com/heavyai/heavydb
www.heavy.ai

azure.microsoft.com/en-us/services/storage/tables

rocksdb.org

Technical documentation

www.claris.com/resources/documentation

docs.heavy.ai

github.com/facebook/rocksdb/wiki

Developer

Claris

a subsidiary of Apple

HEAVY.AI, Inc.

Microsoft

Facebook, Inc.

Initial release

1983

2016

2012

2013

Current release

19.4.1, November 2021

5.10, January 2022

9.2.1, May 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; enterprise edition available

commercial

Open Source

BSD

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

C++ and CUDA

C++

Server operating systems

iOS

client part only
Linux
OS X
Windows

Linux

hosted

Linux

Data scheme

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.

yes

A http query request can return the data in XML format

Secondary indexes

yes

SQL

Support of SQL

yes

via plugins

yes

APIs and other access methods

Filemaker WebDirect
JDBC
ODBC

JDBC
ODBC
Thrift
Vega

RESTful HTTP API

C++ API
Java API

Supported programming languages

PHP

All languages supporting JDBC/ODBC/Thrift
Python

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

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Round robin

Sharding

Implicit feature of the cloud service

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication, warm standby

since Version 14

Multi-source replication

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

optimistic locking

yes

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

fine grained access rights according to SQL-standard

Access rights based on private key authentication or shared access signatures

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