DBMS > Percona Server for MySQL vs. Snowflake vs. Solr vs. Tigris

System Properties Comparison Percona Server for MySQL vs. Snowflake vs. Solr vs. Tigris

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Editorial information provided by DB-Engines

Name

Description

Enhanced drop-in replacement for MySQL based on XtraDB or TokuDB storage engines with improved performance and additional diagnostic and management features.

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

A widely used distributed, scalable search engine based on Apache Lucene

A horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructure

Primary database model

Relational DBMS

Search engine

Document store
Key-value store
Search engine
Time Series DBMS

Secondary database models

Spatial DBMS

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

Score	2.03
Rank	#122	Overall
	#57	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	42.91
Rank	#24	Overall
	#3	Search engines

Score	0.02
Rank	#369	Overall
	#51	Document stores
	#55	Key-value stores
	#24	Search engines
	#38	Time Series DBMS

Website

www.percona.com/software/mysql-database/percona-server

www.snowflake.com

solr.apache.org

www.tigrisdata.com

Technical documentation

www.percona.com/downloads/Percona-Server-LATEST

docs.snowflake.net/manuals/index.html

solr.apache.org/resources.html

www.tigrisdata.com/docs

Developer

Percona

Snowflake Computing Inc.

Apache Software Foundation

Tigris Data, Inc.

Initial release

2008

2014

2006

2022

Current release

8.0.36-28, 2024

9.6.0, April 2024

License

Commercial or Open Source

Open Source

GPL version 2

commercial

Open Source

Apache Version 2

Open Source

Apache Version 2.0

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

C and C++

Java

Server operating systems

Linux

hosted

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Linux
macOS
Windows

Data scheme

yes

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

yes

Dynamic Fields enables on-the-fly addition of new fields

yes

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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

All search fields are automatically indexed

yes

SQL

Support of SQL

yes

Solr Parallel SQL Interface

APIs and other access methods

ADO.NET
JDBC
ODBC

CLI Client
JDBC
ODBC

Java API
RESTful HTTP/JSON API

CLI Client
gRPC
RESTful HTTP API

Supported programming languages

Ada
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

JavaScript (Node.js)
Python

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Go
Java
JavaScript (Node.js)

Server-side scripts

Stored procedures

yes

user defined functions

Java plugins

Triggers

yes

similar concept for controling cloud resources

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication
XtraDB Cluster

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using FoundationDB

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

no user groups or roles

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

yes

Access rights for users and roles

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