DBMS > Altibase vs. Apache Impala vs. Google Cloud Bigtable vs. Snowflake vs. SwayDB

System Properties Comparison Altibase vs. Apache Impala vs. Google Cloud Bigtable vs. Snowflake vs. SwayDB

Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

Analytic DBMS for Hadoop

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

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

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Relational DBMS

Key-value store
Wide column store

Relational DBMS

Key-value store

Secondary database models

Document store

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

Score	1.07
Rank	#186	Overall
	#87	Relational DBMS

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Website

altibase.com

impala.apache.org

cloud.google.com/bigtable

www.snowflake.com

swaydb.simer.au

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

impala.apache.org/impala-docs.html

cloud.google.com/bigtable/docs

docs.snowflake.net/manuals/index.html

Developer

Altibase

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Google

Snowflake Computing Inc.

Simer Plaha

Initial release

1999

2013

2015

2014

2018

Current release

v7.3, 2023, August 2023

4.1.0, June 2022

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

Open Source

Apache Version 2

commercial

Open Source

GNU Affero GPL V3.0

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++

Scala

Server operating systems

AIX
HP-UX
Linux

Linux

hosted

Data scheme

yes

schema-free

yes

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

schema-free

Typing

predefined data types such as float or date

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

SQL

Support of SQL

ANSI SQL-92

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC
Proprietary protocol

JDBC
ODBC

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

CLI Client
JDBC
ODBC

Supported programming languages

C
C++
Java

All languages supporting JDBC/ODBC

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

JavaScript (Node.js)
Python

Java
Kotlin
Scala

Server-side scripts

Stored procedures

stored procedures and stored functions

yes

user defined functions and integration of map-reduce

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Internal replication in Colossus, and regional replication between two clusters in different zones

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic single-row operations

ACID

Atomic execution of operations

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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

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