DBMS > Bangdb vs. FileMaker vs. Newts vs. Postgres-XL vs. Snowflake

System Properties Comparison Bangdb vs. FileMaker vs. Newts vs. Postgres-XL vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

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

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

Time Series DBMS based on Cassandra

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Spatial 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	48.20
Rank	#20	Overall
	#14	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

bangdb.com

www.claris.com/filemaker

opennms.github.io/newts

www.postgres-xl.org

www.snowflake.com

Technical documentation

docs.bangdb.com

www.claris.com/resources/documentation

github.com/OpenNMS/newts/wiki

www.postgres-xl.org/documentation

docs.snowflake.net/manuals/index.html

Developer

Sachin Sinha, BangDB

Claris

a subsidiary of Apple

OpenNMS Group

Snowflake Computing Inc.

Initial release

2012

1983

2014

since 2012, originally named StormDB

2014

Current release

BangDB 2.0, October 2021

19.4.1, November 2021

10 R1, October 2018

License

Commercial or Open Source

Open Source

BSD 3

commercial

Open Source

Apache 2.0

Open Source

Mozilla public license

commercial

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++

Java

Server operating systems

Linux

iOS

client part only
Linux
OS X
Windows

Linux
OS X
Windows

Linux
macOS

hosted

Data scheme

schema-free

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

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

yes

XML type, but no XML query functionality

yes

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

yes

via plugins

yes

distributed, parallel query execution

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

Filemaker WebDirect
JDBC
ODBC

HTTP REST
Java API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

CLI Client
JDBC
ODBC

Supported programming languages

C
C#
C++
Java
Python

PHP

Java

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes, Notifications (with Streaming only)

yes

similar concept for controling cloud resources

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

none

Sharding

based on Cassandra

horizontal partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

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

Source-replica replication, warm standby

since Version 14

selectable replication factor

based on Cassandra

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

MVCC

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

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

yes (enterprise version only)

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

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles and pluggable authentication

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