DBMS > Apache Phoenix vs. Snowflake vs. Spark SQL vs. Splunk vs. VoltDB

System Properties Comparison Apache Phoenix vs. Snowflake vs. Spark SQL vs. Splunk vs. VoltDB

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Name

Description

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

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

Spark SQL is a component on top of 'Spark Core' for structured data processing

Analytics Platform for Big Data

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Relational DBMS

Search engine

Relational DBMS

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

Score	2.06
Rank	#123	Overall
	#58	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	89.10
Rank	#14	Overall
	#2	Search engines

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

Technical documentation

phoenix.apache.org

docs.snowflake.net/manuals/index.html

spark.apache.org/docs/latest/sql-programming-guide.html

docs.splunk.com/Documentation/Splunk

docs.voltdb.com

Developer

Apache Software Foundation

Snowflake Computing Inc.

Apache Software Foundation

Splunk Inc.

VoltDB Inc.

Initial release

2014

2003

2010

Current release

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

3.5.0 ( 2.13), September 2023

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache 2.0

commercial

Limited free edition and free developer edition available

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

Scala

Java, C++

Server operating systems

Linux
Unix
Windows

hosted

Linux
OS X
Windows

Linux
OS X
Solaris
Windows

Linux
OS X

for development

Data scheme

yes

late-bound, schema-on-read capabilities

yes

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

yes

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

Splunk Search Processing Language for search commands

yes

only a subset of SQL 99

APIs and other access methods

JDBC

CLI Client
JDBC
ODBC

JDBC
ODBC

HTTP REST

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

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

JavaScript (Node.js)
Python

Java
Python
R
Scala

C#
Java
JavaScript
PHP
Python
Ruby

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

user defined functions

yes

Java

Triggers

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

yes, utilizing Spark Core

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

none

Multi-source replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

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

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

Access rights for users and roles

Users and roles with access to stored procedures

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