DBMS > Apache Phoenix vs. BigObject vs. SAP HANA vs. Snowflake

System Properties Comparison Apache Phoenix vs. BigObject vs. SAP HANA vs. Snowflake

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Name

Description

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

Analytic DBMS for real-time computations and queries

In-memory, column based data store. Available as appliance or cloud service

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

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	2.06
Rank	#123	Overall
	#58	Relational DBMS

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

phoenix.apache.org

bigobject.io

www.sap.com/products/hana.html

www.snowflake.com

Technical documentation

phoenix.apache.org

docs.bigobject.io

help.sap.com/hana

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation

BigObject, Inc.

SAP

Snowflake Computing Inc.

Initial release

2014

2015

2010

2014

Current release

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

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free community edition available

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

Linux
Unix
Windows

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Appliance or cloud-service

hosted

Data scheme

yes

late-bound, schema-on-read capabilities

yes

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

Typing

predefined data types such as float or date

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

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC

fluentd
ODBC
RESTful HTTP API

JDBC
ODBC

CLI Client
JDBC
ODBC

Supported programming languages

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

Lua

SQLScript, R

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

yes

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

none

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

User concepts

Access control

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

yes

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

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