DBMS > Bangdb vs. Newts vs. Solr vs. YottaDB

System Properties Comparison Bangdb vs. Newts vs. Solr vs. YottaDB

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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

Time Series DBMS based on Cassandra

A widely used distributed, scalable search engine based on Apache Lucene

A fast and solid embedded Key-value store

Primary database model

Document store
Graph DBMS
Time Series DBMS

Time Series DBMS

Search engine

Key-value store

Secondary database models

Spatial DBMS

Relational DBMS

using the Octo plugin

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	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	42.91
Rank	#24	Overall
	#3	Search engines

Score	0.20
Rank	#317	Overall
	#47	Key-value stores

Website

bangdb.com

opennms.github.io/newts

solr.apache.org

yottadb.com

Technical documentation

docs.bangdb.com

github.com/OpenNMS/newts/wiki

solr.apache.org/resources.html

yottadb.com/resources/documentation

Developer

Sachin Sinha, BangDB

OpenNMS Group

Apache Software Foundation

YottaDB, LLC

Initial release

2012

2014

2006

2001

Current release

BangDB 2.0, October 2021

9.6.0, April 2024

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Apache 2.0

Open Source

Apache Version 2

Open Source

AGPL 3.0

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

Server operating systems

Linux

Linux
OS X
Windows

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Docker
Linux

Data scheme

schema-free

yes

Dynamic Fields enables on-the-fly addition of new fields

schema-free

Typing

predefined data types such as float or date

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

yes

supports customizable data types and automatic typing

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

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

All search fields are automatically indexed

SQL

Support of SQL

SQL like support with command line tool

Solr Parallel SQL Interface

by using the Octo plugin

APIs and other access methods

Proprietary protocol
RESTful HTTP API

HTTP REST
Java API

Java API
RESTful HTTP/JSON API

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

C
C#
C++
Java
Python

Java

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

Java plugins

Triggers

yes, Notifications (with Streaming only)

yes

User configurable commands triggered on index changes

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

based on Cassandra

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

selectable replication factor

based on Cassandra

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

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

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

optimistic locking

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

yes

User concepts

Access control

yes (enterprise version only)

yes

Users and groups based on OS-security mechanisms

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More resources

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