DBMS > Amazon DynamoDB vs. Couchbase vs. FileMaker vs. GridGain

System Properties Comparison Amazon DynamoDB vs. Couchbase vs. FileMaker vs. GridGain

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Editorial information provided by DB-Engines

Name

Description

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

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

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

GridGain is an in-memory computing platform, built on Apache Ignite

Primary database model

Document store
Key-value store

Document store

Relational DBMS

Key-value store
Relational DBMS

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector 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	16.59
Rank	#36	Overall
	#5	Document stores

Score	47.91
Rank	#20	Overall
	#14	Relational DBMS

Score	1.55
Rank	#150	Overall
	#26	Key-value stores
	#70	Relational DBMS

Website

aws.amazon.com/dynamodb

www.couchbase.com

www.claris.com/filemaker

www.gridgain.com

Technical documentation

docs.aws.amazon.com/dynamodb

docs.couchbase.com

www.claris.com/resources/documentation

www.gridgain.com/docs/index.html

Developer

Amazon

Couchbase, Inc.

Claris

a subsidiary of Apple

GridGain Systems, Inc.

Initial release

2012

2011

1983

2007

Current release

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

19.4.1, November 2021

GridGain 8.5.1

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

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

C, C++, Go and Erlang

Java, C++, .Net

Server operating systems

hosted

Linux
OS X
Windows

iOS

client part only
Linux
OS X
Windows

Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

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

Secondary indexes

yes

SQL

Support of SQL

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

yes

via plugins

ANSI-99 for query and DML statements, subset of DDL

APIs and other access methods

RESTful HTTP API

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

Filemaker WebDirect
JDBC
ODBC

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

PHP

C#
C++
Java
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

yes

yes (compute grid and cache interceptors can be used instead)

Triggers

yes

by integration with AWS Lambda

yes

via the TAP protocol

yes

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

including cross data center replication
Source-replica replication

Source-replica replication, warm standby

since Version 14

yes (replicated cache)

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency

Foreign keys

Referential integrity

yes

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

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

Ephemeral buckets

yes

User concepts

Access control

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

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

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

Security Hooks for custom implementations

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