DBMS > Cubrid vs. Fauna vs. jBASE vs. Snowflake vs. Solr

System Properties Comparison Cubrid vs. Fauna vs. jBASE vs. Snowflake vs. Solr

Editorial information provided by DB-Engines

Name

Description

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.

A robust multi-value DBMS comprising development tools and middleware

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

Relational DBMS

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Multivalue DBMS

Relational DBMS

Search engine

Secondary database models

Spatial DBMS

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

Score	1.04
Rank	#187	Overall
	#87	Relational DBMS

Score	1.55
Rank	#151	Overall
	#26	Document stores
	#14	Graph DBMS
	#71	Relational DBMS
	#13	Time Series DBMS

Score	1.49
Rank	#156	Overall
	#3	Multivalue DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	41.02
Rank	#24	Overall
	#3	Search engines

Website

cubrid.com (korean)
cubrid.org (english)

fauna.com

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

www.snowflake.com

solr.apache.org

Technical documentation

cubrid.org/manuals

docs.fauna.com

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

docs.snowflake.net/manuals/index.html

solr.apache.org/resources.html

Developer

CUBRID Corporation, CUBRID Foundation

Fauna, Inc.

Rocket Software (formerly Zumasys)

Snowflake Computing Inc.

Apache Software Foundation

Initial release

2008

2014

1991

2014

2006

Current release

11.0, January 2021

5.7

9.6.1, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 2

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, C++, Java

Scala

Java

Server operating systems

Linux
Windows

hosted

AIX
Linux
Windows

hosted

All OS with a Java VM

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

Data scheme

yes

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

optional

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

yes

Embedded SQL for jBASE in BASIC

yes

Solr Parallel SQL Interface

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

RESTful HTTP API

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

CLI Client
JDBC
ODBC

Java API
RESTful HTTP/JSON API

Supported programming languages

C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

.Net
Basic
Jabbascript
Java

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 Stored Procedures

user defined functions

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

none

horizontal partitioning

consistent hashing

Sharding

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

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

Foreign keys

Referential integrity

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

User concepts

Access control

fine grained access rights according to SQL-standard

Identity management, authentication, and access control

Access rights can be defined down to the item level

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

yes

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.