DBMS > FileMaker vs. Hive vs. Machbase Neo vs. Oracle vs. TigerGraph

System Properties Comparison FileMaker vs. Hive vs. Machbase Neo vs. Oracle vs. TigerGraph

Editorial information provided by DB-Engines

Name

Description

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

data warehouse software for querying and managing large distributed datasets, built on Hadoop

TimeSeries DBMS for AIoT and BigData

Widely used RDBMS

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Secondary database models

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	48.20
Rank	#20	Overall
	#14	Relational DBMS

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	0.12
Rank	#339	Overall
	#30	Time Series DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	1.83
Rank	#139	Overall
	#13	Graph DBMS

Website

www.claris.com/filemaker

hive.apache.org

machbase.com

www.oracle.com/database

www.tigergraph.com

Technical documentation

www.claris.com/resources/documentation

cwiki.apache.org/confluence/display/Hive/Home

machbase.com/dbms

docs.oracle.com/en/database

docs.tigergraph.com

Developer

Claris

a subsidiary of Apple

Apache Software Foundation

initially developed by Facebook

Machbase

Oracle

Initial release

1983

2012

2013

1980

2017

Current release

19.4.1, November 2021

3.1.3, April 2022

V8.0, August 2023

23c, September 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

commercial

free test version available

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C and C++

C++

Server operating systems

iOS

client part only
Linux
OS X
Windows

All OS with a Java VM

Linux
macOS
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Linux

Data scheme

yes

Schemaless in JSON and XML columns

yes

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

yes

Secondary indexes

yes

SQL

Support of SQL

yes

via plugins

SQL-like DML and DDL statements

SQL-like query language

yes

with proprietary extensions

SQL-like query language (GSQL)

APIs and other access methods

Filemaker WebDirect
JDBC
ODBC

JDBC
ODBC
Thrift

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

PHP

C++
Java
PHP
Python

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

C++
Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

PL/SQL

also stored procedures in Java possible

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication, warm standby

since Version 14

selectable replication factor

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

can be realized in PL/SQL

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

isolation level can be parameterized

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

volatile and lookup table

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

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

Access rights for users, groups and roles

simple password-based access control

fine grained access rights according to SQL-standard

Role-based access control

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