DBMS > Apache Phoenix vs. EXASOL vs. GigaSpaces vs. Snowflake vs. STSdb

System Properties Comparison Apache Phoenix vs. EXASOL vs. GigaSpaces vs. Snowflake vs. STSdb

Editorial information provided by DB-Engines

Name

Description

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

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Relational DBMS

Document store
Object oriented DBMS

Values are user defined objects

Relational DBMS

Key-value store

Secondary database models

Graph DBMS
Search engine

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

Score	2.06
Rank	#123	Overall
	#58	Relational DBMS

Score	1.76
Rank	#139	Overall
	#62	Relational DBMS

Score	1.03
Rank	#188	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Website

github.com/STSSoft/STSdb4

Technical documentation

phoenix.apache.org

www.exasol.com/resources

docs.gigaspaces.com/latest/landing.html

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation

Exasol

Gigaspaces Technologies

Snowflake Computing Inc.

STS Soft SC

Initial release

2014

2000

2014

2011

Current release

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

15.5, September 2020

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 2; Commercial licenses available

commercial

Open Source

GPLv2, commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Java, C++, .Net

Server operating systems

Linux
Unix
Windows

Linux
macOS
Solaris
Windows

hosted

Windows

Data scheme

yes

late-bound, schema-on-read capabilities

yes

schema-free

yes

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

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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.

XML can be used for describing objects metadata

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-99 for query and DML statements

yes

APIs and other access methods

JDBC

.Net
JDBC
ODBC
WebSocket

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

CLI Client
JDBC
ODBC

.NET Client API

Supported programming languages

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

Java
Lua
Python
R

.Net
C++
Java
Python
Scala

JavaScript (Node.js)
Python

C#
Java

Server-side scripts

Stored procedures

user defined functions

yes

user defined functions

Triggers

yes

yes, event driven architecture

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

Hadoop integration

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

User concepts

Access control

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

Access rights for users, groups and roles according to SQL-standard

Role-based access control

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

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