DBMS > Apache Impala vs. FeatureBase vs. OrigoDB vs. Snowflake

System Properties Comparison Apache Impala vs. FeatureBase vs. OrigoDB vs. Snowflake

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.

A fully ACID in-memory object graph database

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

Primary database model

Relational DBMS

Document store
Object oriented DBMS

Relational DBMS

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	0.31
Rank	#292	Overall
	#135	Relational DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#19	Object oriented DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

Technical documentation

impala.apache.org/impala-docs.html

docs.featurebase.com

origodb.com/docs

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Molecula and Pilosa Open Source Contributors

Robert Friberg et al

Snowflake Computing Inc.

Initial release

2013

2017

2009

under the name LiveDB

2014

Current release

4.1.0, June 2022

2022, May 2022

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

commercial

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++

Server operating systems

Linux

Linux
macOS

Linux
Windows

hosted

Data scheme

yes

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

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL queries

yes

APIs and other access methods

JDBC
ODBC

gRPC
JDBC
Kafka Connector
ODBC

.NET Client API
HTTP API
LINQ

CLI Client
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

Java
Python

.Net

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

user defined functions

Triggers

yes

Domain Events

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

client side managed; servers are not synchronized

yes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

Source-replica replication

yes

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

Immediate Consistency

Foreign keys

Referential integrity

yes

depending on model

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using Linux fsync

yes

Write ahead log

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Role based authorization

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

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