DBMS > Amazon DynamoDB vs. Bangdb vs. Databricks vs. FileMaker vs. Memcached

System Properties Comparison Amazon DynamoDB vs. Bangdb vs. Databricks vs. FileMaker vs. Memcached

Editorial information provided by DB-Engines

Name

Description

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

Converged and high performance database for device data, events, time series, document and graph

The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.

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

In-memory key-value store, originally intended for caching

Primary database model

Document store
Key-value store

Document store
Graph DBMS
Time Series DBMS

Document store
Relational DBMS

Relational DBMS

Key-value store

Secondary database models

Spatial 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	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	81.08
Rank	#15	Overall
	#2	Document stores
	#10	Relational DBMS

Score	47.91
Rank	#20	Overall
	#14	Relational DBMS

Score	18.08
Rank	#32	Overall
	#4	Key-value stores

Website

aws.amazon.com/dynamodb

bangdb.com

www.databricks.com

www.claris.com/filemaker

www.memcached.org

Technical documentation

docs.aws.amazon.com/dynamodb

docs.bangdb.com

docs.databricks.com

www.claris.com/resources/documentation

github.com/memcached/memcached/wiki

Developer

Amazon

Sachin Sinha, BangDB

Databricks

Claris

a subsidiary of Apple

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Initial release

2012

2013

1983

2003

Current release

BangDB 2.0, October 2021

19.4.1, November 2021

1.6.27, May 2024

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

BSD 3

commercial

Open Source

BSD license

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

Server operating systems

hosted

Linux

hosted

iOS

client part only
Linux
OS X
Windows

FreeBSD
Linux
OS X
Unix
Windows

Data scheme

schema-free

Flexible Schema (defined schema, partial schema, schema free)

yes

schema-free

Typing

predefined data types such as float or date

yes

yes: string, long, double, int, geospatial, stream, events

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

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

with Databricks SQL

yes

via plugins

APIs and other access methods

RESTful HTTP API

Proprietary protocol
RESTful HTTP API

JDBC
ODBC
RESTful HTTP API

Filemaker WebDirect
JDBC
ODBC

Proprietary protocol

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C
C#
C++
Java
Python

Python
R
Scala

PHP

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

Triggers

yes

by integration with AWS Lambda

yes, Notifications (with Streaming only)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor, Knob for CAP (enterprise version only)

yes

Source-replica replication, warm standby

since Version 14

none

Repcached, a Memcached patch, provides this functionallity

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Tunable consistency, set CAP knob accordingly

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

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes, run db with in-memory only mode

User concepts

Access control

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

yes (enterprise version only)

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

yes

using SASL (Simple Authentication and Security Layer) protocol

More information provided by the system vendor

Specific characteristics

Supported database models : In addition to the Document store and Relational DBMS...
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