DBMS > Apache Impala vs. Faircom DB vs. Realm vs. Snowflake vs. STSdb

System Properties Comparison Apache Impala vs. Faircom DB vs. Realm vs. Snowflake vs. STSdb

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Document store

Relational DBMS

Key-value store

Secondary database models

Document store

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	0.29
Rank	#304	Overall
	#43	Key-value stores
	#136	Relational DBMS

Score	7.41
Rank	#52	Overall
	#8	Document stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Website

impala.apache.org

www.faircom.com/products/faircom-db

realm.io

www.snowflake.com

github.com/STSSoft/STSdb4

Technical documentation

impala.apache.org/impala-docs.html

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

realm.io/docs

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

FairCom Corporation

Realm, acquired by MongoDB in May 2019

Snowflake Computing Inc.

STS Soft SC

Initial release

2013

1979

2014

2011

Current release

4.1.0, June 2022

V12, November 2020

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Restricted, free version available

Open Source

commercial

Open Source

GPLv2, commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

ANSI C, C++

Server operating systems

Linux

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

Android
Backend: server-less
iOS
Windows

hosted

Windows

Data scheme

yes

schema free, schema optional, schema required, partial schema,

yes

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

yes

Typing

predefined data types such as float or date

yes

yes, ANSI SQL Types, JSON, typed binary structures

yes

primitive types and user defined types (classes)

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

SQL-like DML and DDL statements

yes, ANSI SQL with proprietary extensions

yes

APIs and other access methods

JDBC
ODBC

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

CLI Client
JDBC
ODBC

.NET Client API

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

.Net
Java

with Android only
Objective-C
React Native
Swift

JavaScript (Node.js)
Python

C#
Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

.Net, JavaScript, C/C++

runs within the applications so server-side scripts are unnecessary

user defined functions

Triggers

yes

Change Listeners

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

none

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

none

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

tunable from ACID to Eventually Consistent

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Yes, tunable from durable to delayed durability to in-memory

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

In-Memory realm

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Fine grained access rights according to SQL-standard with additional protections for files

yes

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

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