DBMS > Apache Phoenix vs. Bangdb vs. Dragonfly vs. Yanza

System Properties Comparison Apache Phoenix vs. Bangdb vs. Dragonfly vs. Yanza

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Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

A scale-out RDBMS with evolutionary schema built on Apache HBase

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

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

Time Series DBMS for IoT Applications

Primary database model

Relational DBMS

Document store
Graph DBMS
Time Series DBMS

Key-value store

Time Series DBMS

Secondary database models

Spatial DBMS

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

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

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

Score	0.41
Rank	#266	Overall
	#38	Key-value stores

Website

phoenix.apache.org

bangdb.com

github.com/dragonflydb/dragonfly
www.dragonflydb.io

yanza.com

Technical documentation

phoenix.apache.org

docs.bangdb.com

www.dragonflydb.io/docs

Developer

Apache Software Foundation

Sachin Sinha, BangDB

DragonflyDB team and community contributors

Yanza

Initial release

2014

2012

2023

2015

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

BangDB 2.0, October 2021

1.0, March 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

BSD 3

Open Source

BSL 1.1

commercial

free version available

Cloud-based only

Only available as a cloud service

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C, C++

C++

Server operating systems

Linux
Unix
Windows

Linux

Windows

Data scheme

yes

late-bound, schema-on-read capabilities

schema-free

scheme-free

schema-free

Typing

predefined data types such as float or date

yes

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

strings, hashes, lists, sets, sorted sets, bit arrays

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.

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

SQL

Support of SQL

yes

SQL like support with command line tool

APIs and other access methods

JDBC

Proprietary protocol
RESTful HTTP API

Proprietary protocol

RESP - REdis Serialization Protocol

HTTP API

Supported programming languages

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

C
C#
C++
Java
Python

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

any language that supports HTTP calls

Server-side scripts

Stored procedures

user defined functions

Lua

Triggers

yes, Notifications (with Streaming only)

publish/subscribe channels provide some trigger functionality

yes

Timer and event based

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

Multi-source replication
Source-replica replication

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

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Tunable consistency, set CAP knob accordingly

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Atomic execution of command blocks and scripts

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes, strict serializability by the server

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

yes, run db with in-memory only mode

yes

User concepts

Access control

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

yes (enterprise version only)

Password-based authentication

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More resources

DB-Engines blog posts

Cloudera's HBase PaaS offering now supports Complex Transactions
11 August 2021, Krishna Maheshwari (sponsor)

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