DBMS > Graphite vs. Hawkular Metrics vs. Snowflake vs. Sphinx vs. Splice Machine

System Properties Comparison Graphite vs. Hawkular Metrics vs. Snowflake vs. Sphinx vs. Splice Machine

Editorial information provided by DB-Engines

Name

Description

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

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

Open source search engine for searching in data from different sources, e.g. relational databases

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

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

Score	4.83
Rank	#67	Overall
	#4	Time Series DBMS

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	5.95
Rank	#55	Overall
	#5	Search engines

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Website

github.com/graphite-project/graphite-web

Technical documentation

graphite.readthedocs.io

www.hawkular.org/hawkular-metrics/docs/user-guide

docs.snowflake.net/manuals/index.html

sphinxsearch.com/docs

splicemachine.com/how-it-works

Developer

Chris Davis

Community supported by Red Hat

Snowflake Computing Inc.

Sphinx Technologies Inc.

Splice Machine

Initial release

2006

2014

2001

2014

Current release

3.5.1, February 2023

3.1, March 2021

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

commercial

Open Source

GPL version 2, commercial licence available

Open Source

AGPL 3.0, commercial license available

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

Python

Java

C++

Java

Server operating systems

Linux
Unix

Linux
OS X
Windows

hosted

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

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

yes

Typing

predefined data types such as float or date

Numeric data only

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

full-text index on all search fields

yes

SQL

Support of SQL

yes

SQL-like query language (SphinxQL)

yes

APIs and other access methods

HTTP API
Sockets

HTTP REST

CLI Client
JDBC
ODBC

Proprietary protocol

JDBC
Native Spark Datasource
ODBC

Supported programming languages

JavaScript (Node.js)
Python

Go
Java
Python
Ruby

JavaScript (Node.js)
Python

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

user defined functions

yes

Java

Triggers

yes

via Hawkular Alerting

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

yes

Sharding

Partitioning is done manually, search queries against distributed index is supported

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

based on Cassandra

yes

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

locking

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Sphinx index.

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

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

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

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