DBMS > Bangdb vs. Elasticsearch vs. FileMaker vs. NSDb

System Properties Comparison Bangdb vs. Elasticsearch vs. FileMaker vs. NSDb

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Editorial information provided by DB-Engines

Name

Description

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

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

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

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Primary database model

Document store
Graph DBMS
Time Series DBMS

Search engine

Relational DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

Document store
Spatial DBMS
Vector DBMS

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

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	135.35
Rank	#7	Overall
	#1	Search engines

Score	48.20
Rank	#20	Overall
	#14	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

bangdb.com

www.elastic.co/elasticsearch

www.claris.com/filemaker

nsdb.io

Technical documentation

docs.bangdb.com

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

www.claris.com/resources/documentation

nsdb.io/Architecture

Developer

Sachin Sinha, BangDB

Elastic

Claris

a subsidiary of Apple

Initial release

2012

2010

1983

2017

Current release

BangDB 2.0, October 2021

8.6, January 2023

19.4.1, November 2021

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Elastic License

commercial

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

Java

Java, Scala

Server operating systems

Linux

All OS with a Java VM

iOS

client part only
Linux
OS X
Windows

Linux
macOS

Data scheme

schema-free

Flexible type definitions. Once a type is defined, it is persistent

yes

Typing

predefined data types such as float or date

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

yes

yes: int, bigint, decimal, string

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

All search fields are automatically indexed

yes

all fields are automatically indexed

SQL

Support of SQL

SQL like support with command line tool

SQL-like query language

yes

via plugins

SQL-like query language

APIs and other access methods

Proprietary protocol
RESTful HTTP API

Java API
RESTful HTTP/JSON API

Filemaker WebDirect
JDBC
ODBC

gRPC
HTTP REST
WebSocket

Supported programming languages

C
C#
C++
Java
Python

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

PHP

Java
Scala

Server-side scripts

Stored procedures

yes

Triggers

yes, Notifications (with Streaming only)

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes

Source-replica replication, warm standby

since Version 14

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

Using Apache Lucene

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

Memcached and Redis integration

User concepts

Access control

yes (enterprise version only)

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

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