DBMS > FileMaker vs. IBM Db2 Event Store vs. TigerGraph vs. Yanza

System Properties Comparison FileMaker vs. IBM Db2 Event Store vs. TigerGraph vs. Yanza

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Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Distributed Event Store optimized for Internet of Things use cases

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

Time Series DBMS for IoT Applications

Primary database model

Relational DBMS

Event Store
Time Series DBMS

Graph DBMS

Time Series DBMS

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

Score	45.20
Rank	#20	Overall
	#14	Relational DBMS

Score	0.18
Rank	#315	Overall
	#2	Event Stores
	#26	Time Series DBMS

Score	1.44
Rank	#152	Overall
	#14	Graph DBMS

Website

www.claris.com/filemaker

www.ibm.com/products/db2-event-store

www.tigergraph.com

yanza.com

Technical documentation

www.claris.com/resources/documentation

www.ibm.com/docs/en/db2-event-store

docs.tigergraph.com

Developer

Claris

a subsidiary of Apple

IBM

Yanza

Initial release

1983

2017

2015

Current release

19.4.1, November 2021

2.0

License

Commercial or Open Source

commercial

free developer edition available

commercial

free version available

Cloud-based only

Only available as a cloud service

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C and C++

C++

Server operating systems

iOS

client part only
Linux
OS X
Windows

Linux

Linux, macOS, Windows for the developer addition

Linux

Windows

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

through the embedded Spark runtime

SQL-like query language (GSQL)

APIs and other access methods

Filemaker WebDirect
JDBC
ODBC

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

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

HTTP API

Supported programming languages

PHP

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

C++
Java

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

Triggers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication, warm standby

since Version 14

Active-active shard replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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

Role-based access control

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More resources

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