DBMS > Blueflood vs. IBM Db2 warehouse vs. Microsoft Access vs. Snowflake vs. Spark SQL

System Properties Comparison Blueflood vs. IBM Db2 warehouse vs. Microsoft Access vs. Snowflake vs. Spark SQL

Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

Cloud-based data warehousing service

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

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

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Time Series DBMS

Relational DBMS

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Trend Chart

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	1.30
Rank	#164	Overall
	#75	Relational DBMS

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Website

blueflood.io

www.ibm.com/products/db2/warehouse

www.microsoft.com/en-us/microsoft-365/access

www.snowflake.com

spark.apache.org/sql

Technical documentation

github.com/rax-maas/blueflood/wiki

developer.microsoft.com/en-us/access

docs.snowflake.net/manuals/index.html

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Rackspace

IBM

Microsoft

Snowflake Computing Inc.

Apache Software Foundation

Initial release

2013

2014

1992

2014

Current release

1902 (16.0.11328.20222), March 2019

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Bundled with Microsoft Office

commercial

Open Source

Apache 2.0

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

Java

C++

Scala

Server operating systems

Linux
OS X

hosted

Windows

Not a real database server, but making use of DLLs

hosted

Linux
OS X
Windows

Data scheme

predefined scheme

yes

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

yes

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.

Import/export of XML data possible

yes

Secondary indexes

yes

SQL

Support of SQL

yes

but not compliant to any SQL standard

yes

SQL-like DML and DDL statements

APIs and other access methods

HTTP REST

.NET Client API
JDBC
ODBC
OLE DB

ADO.NET
DAO
ODBC
OLE DB

CLI Client
JDBC
ODBC

JDBC
ODBC

Supported programming languages

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

JavaScript (Node.js)
Python

Java
Python
R
Scala

Server-side scripts

Stored procedures

PL/SQL, SQL PL

yes

since Access 2010 using the ACE-engine

user defined functions

Triggers

yes

since Access 2010 using the ACE-engine

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

none

yes

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes

none

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

but no files for transaction logging

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

but no files for transaction logging

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

a simple user-level security was built in till version Access 2003

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

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