DBMS > Apache Phoenix vs. Bangdb vs. InfinityDB vs. Pinecone

System Properties Comparison Apache Phoenix vs. Bangdb vs. InfinityDB vs. Pinecone

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Editorial information provided by DB-Engines

Name

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 Java embedded Key-Value Store which extends the Java Map interface

A managed, cloud-native vector database

Primary database model

Relational DBMS

Document store
Graph DBMS
Time Series DBMS

Key-value store

Vector 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	0.00
Rank	#378	Overall
	#57	Key-value stores

Score	3.16
Rank	#95	Overall
	#2	Vector DBMS

Website

Technical documentation

phoenix.apache.org

docs.bangdb.com

boilerbay.com/infinitydb/manual

docs.pinecone.io/docs/overview

Developer

Apache Software Foundation

Sachin Sinha, BangDB

Boiler Bay Inc.

Pinecone Systems, Inc

Initial release

2014

2012

2002

2019

Current release

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

BangDB 2.0, October 2021

4.0

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

BSD 3

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C, C++

Java

Server operating systems

Linux
Unix
Windows

Linux

All OS with a Java VM

hosted

Data scheme

yes

late-bound, schema-on-read capabilities

schema-free

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

Typing

predefined data types such as float or date

yes

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

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

String, Number, Boolean

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

manual creation possible, using inversions based on multi-value capability

SQL

Support of SQL

yes

SQL like support with command line tool

APIs and other access methods

JDBC

Proprietary protocol
RESTful HTTP API

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

RESTful HTTP API

Supported programming languages

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

C
C#
C++
Java
Python

Java

Python

Server-side scripts

Stored procedures

user defined functions

Triggers

yes, Notifications (with Streaming only)

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)

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

Immediate Consistency

READ-COMMITTED or SERIALIZED

Foreign keys

Referential integrity

manual creation possible, using inversions based on multi-value capability

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

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

yes, run db with in-memory only mode

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)

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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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Vector databases
2 June 2023, Matthias Gelbmann

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