DBMS > Dragonfly vs. FileMaker vs. Newts vs. Oracle vs. TigerGraph

System Properties Comparison Dragonfly vs. FileMaker vs. Newts vs. Oracle vs. TigerGraph

Editorial information provided by DB-Engines

Name

Description

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

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

Time Series DBMS based on Cassandra

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	0.41
Rank	#266	Overall
	#38	Key-value stores

Score	48.20
Rank	#20	Overall
	#14	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	1.83
Rank	#139	Overall
	#13	Graph DBMS

Website

github.com/dragonflydb/dragonfly
www.dragonflydb.io

www.claris.com/filemaker

opennms.github.io/newts

www.oracle.com/database

www.tigergraph.com

Technical documentation

www.dragonflydb.io/docs

www.claris.com/resources/documentation

github.com/OpenNMS/newts/wiki

docs.oracle.com/en/database

docs.tigergraph.com

Developer

DragonflyDB team and community contributors

Claris

a subsidiary of Apple

OpenNMS Group

Oracle

Initial release

2023

1983

2014

1980

2017

Current release

1.0, March 2023

19.4.1, November 2021

23c, September 2023

License

Commercial or Open Source

Open Source

BSL 1.1

commercial

Open Source

Apache 2.0

commercial

restricted free version is available

commercial

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

C++

Java

C and C++

C++

Server operating systems

Linux

iOS

client part only
Linux
OS X
Windows

Linux
OS X
Windows

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

Linux

Data scheme

scheme-free

yes

schema-free

yes

Schemaless in JSON and XML columns

yes

Typing

predefined data types such as float or date

strings, hashes, lists, sets, sorted sets, bit arrays

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

yes

with proprietary extensions

SQL-like query language (GSQL)

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

Filemaker WebDirect
JDBC
ODBC

HTTP REST
Java API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

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

Supported programming languages

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

PHP

Java

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

Lua

yes

PL/SQL

also stored procedures in Java possible

yes

Triggers

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Source-replica replication, warm standby

since Version 14

selectable replication factor

based on Cassandra

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

Atomic execution of command blocks and scripts

ACID

isolation level can be parameterized

ACID

Concurrency

Support for concurrent manipulation of data

yes, strict serializability by the server

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

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

User concepts

Access control

Password-based authentication

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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