DBMS > Dgraph vs. FileMaker vs. Google Cloud Datastore vs. ToroDB vs. VelocityDB

System Properties Comparison Dgraph vs. FileMaker vs. Google Cloud Datastore vs. ToroDB vs. VelocityDB

Editorial information provided by DB-Engines

Name

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

Description

Distributed and scalable native Graph DBMS

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

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

A MongoDB-compatible JSON document store, built on top of PostgreSQL

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Graph DBMS

Relational DBMS

Document store

Graph DBMS
Object oriented DBMS

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

Score	1.48
Rank	#158	Overall
	#15	Graph DBMS

Score	49.73
Rank	#20	Overall
	#14	Relational DBMS

Score	4.49
Rank	#79	Overall
	#12	Document stores

Score	0.11
Rank	#347	Overall
	#35	Graph DBMS
	#15	Object oriented DBMS

Website

dgraph.io

www.claris.com/filemaker

cloud.google.com/datastore

github.com/torodb/server

velocitydb.com

Technical documentation

dgraph.io/docs

www.claris.com/resources/documentation

cloud.google.com/datastore/docs

velocitydb.com/UserGuide

Developer

Dgraph Labs, Inc.

Claris

a subsidiary of Apple

Google

8Kdata

VelocityDB Inc

Initial release

2016

1983

2008

2016

2011

Current release

19.4.1, November 2021

7.x

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

AGPL-V3

commercial

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

Java

Server operating systems

Linux
OS X
Windows

iOS

client part only
Linux
OS X
Windows

hosted

All OS with a Java 7 VM

Any that supports .NET

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, details here

yes

string, integer, double, boolean, date, object_id

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

SQL-like query language (GQL)

APIs and other access methods

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

Filemaker WebDirect
JDBC
ODBC

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

.Net

Supported programming languages

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

PHP

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net

Server-side scripts

Stored procedures

yes

using Google App Engine

Triggers

yes

Callbacks using the Google Apps Engine

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

yes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

Source-replica replication, warm standby

since Version 14

Multi-source replication using Paxos

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

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

User concepts

Access control

Planned for future releases

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

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Access rights for users and roles

Based on Windows Authentication

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