DBMS > Datastax Enterprise vs. Microsoft Access vs. SiriDB vs. Snowflake vs. Warp 10

System Properties Comparison Datastax Enterprise vs. Microsoft Access vs. SiriDB vs. Snowflake vs. Warp 10

Editorial information provided by DB-Engines

Name

Description

DataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.

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.)

Open Source Time Series DBMS

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

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS

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Score	5.80
Rank	#60	Overall
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Score	104.92
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	#8	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.07
Rank	#349	Overall
	#32	Time Series DBMS

Website

www.datastax.com/products/datastax-enterprise

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

siridb.com

www.snowflake.com

www.warp10.io

Technical documentation

docs.datastax.com

developer.microsoft.com/en-us/access

docs.siridb.com

docs.snowflake.net/manuals/index.html

www.warp10.io/content/02_Getting_started

Developer

DataStax

Microsoft

Cesbit

Snowflake Computing Inc.

SenX

Initial release

2011

1992

2017

2014

2015

Current release

6.8, April 2020

1902 (16.0.11328.20222), March 2019

License

Commercial or Open Source

commercial

Bundled with Microsoft Office

Open Source

MIT License

commercial

Open Source

Apache License 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.

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Implementation language

Java

C++

Java

Server operating systems

Linux
OS X

Windows

Not a real database server, but making use of DLLs

Linux

hosted

Linux
OS X
Windows

Data scheme

schema-free

yes

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

schema-free

Typing

predefined data types such as float or date

yes

Numeric data

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

SQL-like DML and DDL statements (CQL); Spark SQL

yes

but not compliant to any SQL standard

yes

APIs and other access methods

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

ADO.NET
DAO
ODBC
OLE DB

HTTP API

CLI Client
JDBC
ODBC

HTTP API
Jupyter
WebSocket

Supported programming languages

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

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

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

since Access 2010 using the ACE-engine

user defined functions

yes

WarpScript

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

no "single point of failure"

none

Sharding

yes

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware, advanced replication for edge computing

none

yes

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

consistency level can be individually decided with each write operation

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomicity and isolation are supported for single operations

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

Access rights for users can be defined per object

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

simple rights management via user accounts

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

Mandatory use of cryptographic tokens, containing fine-grained authorizations

More information provided by the system vendor

Specific characteristics

DataStax Enterprise is scale-out data infrastructure for enterprises that need to...
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Competitive advantages

Supporting the following application requirements: Zero downtime - Built on Apache...
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Typical application scenarios

Applications that must be massively and linearly scalable with 100% uptime and able...
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Key customers

Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
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Market metrics

Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
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Licensing and pricing models

Annual subscription
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