DBMS > FileMaker vs. Hive vs. Postgres-XL vs. TerarkDB

System Properties Comparison FileMaker vs. Hive vs. Postgres-XL vs. TerarkDB

Please select another system to include it in the comparison.

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

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Relational DBMS

Key-value store

Secondary database models

Document store
Spatial DBMS

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	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

www.claris.com/filemaker

hive.apache.org

www.postgres-xl.org

github.com/bytedance/terarkdb

Technical documentation

www.claris.com/resources/documentation

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

www.postgres-xl.org/documentation

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Claris

a subsidiary of Apple

Apache Software Foundation

initially developed by Facebook

ByteDance, originally Terark

Initial release

1983

2012

2014

since 2012, originally named StormDB

2016

Current release

19.4.1, November 2021

3.1.3, April 2022

10 R1, October 2018

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

Mozilla public license

commercial

restricted open source version available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C++

Server operating systems

iOS

client part only
Linux
OS X
Windows

All OS with a Java VM

Linux
macOS

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

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

via plugins

SQL-like DML and DDL statements

yes

distributed, parallel query execution

APIs and other access methods

Filemaker WebDirect
JDBC
ODBC

JDBC
ODBC
Thrift

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

C++ API
Java API

Supported programming languages

PHP

C++
Java
PHP
Python

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C++
Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication, warm standby

since Version 14

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

MVCC

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

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Why is Hadoop not listed in the DB-Engines Ranking?
13 May 2013, Paul Andlinger

show all

Recent citations in the news

Tilda Swinton on 'Problemista' Fan Horror Stories About Her Character
1 March 2024, IndieWire

Reviews - Features
1 March 2024, Reverse Shot

Apple Filed for new Trademarks in the U.S. and Hong Kong this week for the Figurative Version of 'Reality Composer ...
15 October 2023, Patently Apple

Apple subsidiary FileMaker returns to its original name from the '80s
6 August 2019, The Verge

Claris FileMaker Pro 19 review
2 March 2022, TechRadar

provided by Google News

Apache Software Foundation Announces Apache Hive 4.0
30 April 2024, Datanami

ASF Unveils the Next Evolution of Big Data Processing With the Launch of Hive 4.0
2 May 2024, Datanami

Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS | Amazon Web Services
18 October 2023, AWS Blog

18 Top Big Data Tools and Technologies to Know About in 2024
24 January 2024, TechTarget

Top 80 Hadoop Interview Questions and Answers for 2024
15 February 2024, Simplilearn

provided by Google News

Share this page