DBMS > OrientDB vs. Percona Server for MongoDB vs. Snowflake vs. Solr

System Properties Comparison OrientDB vs. Percona Server for MongoDB vs. Snowflake vs. Solr

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Editorial information provided by DB-Engines

Name

Description

Multi-model DBMS (Document, Graph, Key/Value)

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

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

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

Primary database model

Document store
Graph DBMS
Key-value store

Document store

Relational DBMS

Search engine

Secondary database models

Spatial DBMS

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

Score	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

Score	0.52
Rank	#254	Overall
	#39	Document stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	42.91
Rank	#24	Overall
	#3	Search engines

Website

orientdb.org

www.percona.com/mongodb/software/percona-server-for-mongodb

www.snowflake.com

solr.apache.org

Technical documentation

www.orientdb.com/docs/last/index.html

docs.percona.com/percona-distribution-for-mongodb

docs.snowflake.net/manuals/index.html

solr.apache.org/resources.html

Developer

OrientDB LTD; CallidusCloud; SAP

Percona

Snowflake Computing Inc.

Apache Software Foundation

Initial release

2010

2015

2014

2006

Current release

3.2.29, March 2024

3.4.10-2.10, November 2017

9.5.0, February 2024

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

GPL Version 2

commercial

Open Source

Apache Version 2

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

C++

Java

Server operating systems

All OS with a Java JDK (>= JDK 6)

Linux

hosted

All OS with a Java VM

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

Data scheme

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

schema-free

yes

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

yes

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

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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

SQL

Support of SQL

SQL-like query language, no joins

yes

Solr Parallel SQL Interface

APIs and other access methods

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

proprietary protocol using JSON

CLI Client
JDBC
ODBC

Java API
RESTful HTTP/JSON API

Supported programming languages

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

JavaScript (Node.js)
Python

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

Server-side scripts

Stored procedures

Java, Javascript

JavaScript

user defined functions

Java plugins

Triggers

Hooks

similar concept for controling cloud resources

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

could be achieved with distributed queries

yes

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

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

yes

Transaction concepts

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

ACID

optimistic locking

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

via In-Memory Engine

yes

User concepts

Access control

Access rights for users and roles; record level security configurable

Access rights for users and roles

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

yes

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