DBMS > Amazon DynamoDB vs. FileMaker vs. HugeGraph vs. InfinityDB vs. RavenDB

System Properties Comparison Amazon DynamoDB vs. FileMaker vs. HugeGraph vs. InfinityDB vs. RavenDB

Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

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

A fast-speed and highly-scalable Graph DBMS

A Java embedded Key-Value Store which extends the Java Map interface

Open Source Operational and Transactional Enterprise NoSQL Document Database

Primary database model

Document store
Key-value store

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	47.91
Rank	#20	Overall
	#14	Relational DBMS

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	0.08
Rank	#365	Overall
	#55	Key-value stores

Score	2.84
Rank	#101	Overall
	#18	Document stores

Website

aws.amazon.com/dynamodb

www.claris.com/filemaker

github.com/hugegraph
hugegraph.apache.org

boilerbay.com

ravendb.net

Technical documentation

docs.aws.amazon.com/dynamodb

www.claris.com/resources/documentation

hugegraph.apache.org/docs

boilerbay.com/infinitydb/manual

ravendb.net/docs

Developer

Amazon

Claris

a subsidiary of Apple

Baidu

Boiler Bay Inc.

Hibernating Rhinos

Initial release

2012

1983

2018

2002

2010

Current release

19.4.1, November 2021

0.9

4.0

5.4, July 2022

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

Apache Version 2.0

commercial

Open Source

AGPL version 3, commercial license available

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

hosted

iOS

client part only
Linux
OS X
Windows

Linux
macOS
Unix

All OS with a Java VM

Linux
macOS
Raspberry Pi
Windows

Data scheme

schema-free

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

schema-free

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

also supports composite index and range index

manual creation possible, using inversions based on multi-value capability

yes

SQL

Support of SQL

yes

via plugins

SQL-like query language (RQL)

APIs and other access methods

RESTful HTTP API

Filemaker WebDirect
JDBC
ODBC

Java API
RESTful HTTP API
TinkerPop Gremlin

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

PHP

Groovy
Java
Python

Java

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

Server-side scripts

Stored procedures

yes

asynchronous Gremlin script jobs

yes

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

depending on used storage backend, e.g. Cassandra and HBase

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication, warm standby

since Version 14

yes

depending on used storage backend, e.g. Cassandra and HBase

none

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

via hugegraph-spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency

Immediate Consistency

READ-COMMITTED or SERIALIZED

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Foreign keys

Referential integrity

yes

edges in graph

manual creation possible, using inversions based on multi-value capability

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

ACID

Optimistic locking for transactions; no isolation for bulk loads

ACID, Cluster-wide transaction available

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

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

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

Users, roles and permissions

Authorization levels configured per client per database

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.