DBMS > Apache Phoenix vs. InfinityDB vs. Machbase Neo vs. Qdrant

System Properties Comparison Apache Phoenix vs. InfinityDB vs. Machbase Neo vs. Qdrant

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Editorial information provided by DB-Engines

Name

Description

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

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

TimeSeries DBMS for AIoT and BigData

A high-performance vector database with neural network or semantic-based matching

Primary database model

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

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

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

Score	0.12
Rank	#339	Overall
	#30	Time Series DBMS

Score	1.16
Rank	#175	Overall
	#6	Vector DBMS

Website

phoenix.apache.org

boilerbay.com

machbase.com

github.com/qdrant/qdrant
qdrant.tech

Technical documentation

phoenix.apache.org

boilerbay.com/infinitydb/manual

machbase.com/dbms

qdrant.tech/documentation

Developer

Apache Software Foundation

Boiler Bay Inc.

Machbase

Qdrant

Initial release

2014

2002

2013

2021

Current release

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

4.0

V8.0, August 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free test version available

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Rust

Server operating systems

Linux
Unix
Windows

All OS with a Java VM

Linux
macOS
Windows

Docker
Linux
macOS
Windows

Data scheme

yes

late-bound, schema-on-read capabilities

yes

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

yes

schema-free

Typing

predefined data types such as float or date

yes

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

yes

Numbers, Strings, Geo, 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

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

yes

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

JDBC

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

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

Supported programming languages

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

Java

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

user defined functions

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

selectable replication factor

Collection-level replication

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

Immediate Consistency

READ-COMMITTED or SERIALIZED

Eventual Consistency, tunable consistency

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

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

volatile and lookup table

yes

User concepts

Access control

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

simple password-based access control

Key-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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Recent citations in the news

Supercharge SQL on Your Data in Apache HBase with Apache Phoenix | Amazon Web Services
2 June 2016, AWS Blog

Azure #HDInsight Apache Phoenix now supports Zeppelin
16 August 2018, azure.microsoft.com

Bridge the SQL-NoSQL gap with Apache Phoenix
4 February 2016, InfoWorld

Apache Calcite, FreeMarker, Gora, Phoenix, and Solr updated
27 March 2017, SDTimes.com

Hortonworks Starts Hadoop Summit with Data Platform Update -- ADTmag
28 June 2016, ADT Magazine

provided by Google News

Open source vector database startup Qdrant raises $28M
23 January 2024, TechCrunch

Qdrant offers managed vector database for hybrid clouds
16 April 2024, InfoWorld

Qdrant Announces an Industry-First Hybrid Cloud Offering For Enterprise AI Applications
16 April 2024, businesswire.com

Qdrant Hybrid Cloud is Now Available for OCI Customers: Managed Vector Search Engine for Data-Sensitive AI ...
16 April 2024, Oracle

Why Vector Data Services For AI Are A Moveable Feast
17 April 2024, Forbes

provided by Google News

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