DBMS > Datastax Enterprise vs. Microsoft Access vs. RocksDB vs. VoltDB

System Properties Comparison Datastax Enterprise vs. Microsoft Access vs. RocksDB vs. VoltDB

Please select another system to include it in the comparison.

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.)

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS

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

Score	6.31
Rank	#57	Overall
	#4	Wide column stores

Score	105.40
Rank	#11	Overall
	#8	Relational DBMS

Score	4.00
Rank	#84	Overall
	#11	Key-value stores

Score	1.46
Rank	#159	Overall
	#74	Relational DBMS

Website

www.datastax.com/products/datastax-enterprise

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

rocksdb.org

www.voltdb.com

Technical documentation

docs.datastax.com

developer.microsoft.com/en-us/access

github.com/facebook/rocksdb/wiki

docs.voltdb.com

Developer

DataStax

Microsoft

Facebook, Inc.

VoltDB Inc.

Initial release

2011

1992

2013

2010

Current release

6.8, April 2020

1902 (16.0.11328.20222), March 2019

8.11.4, April 2024

11.3, April 2022

License

Commercial or Open Source

commercial

Bundled with Microsoft Office

Open Source

BSD

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Datastax Astra DB: Astra DB simplifies cloud-native Cassandra application development for your apps, microservices and functions. Deploy in minutes on AWS, Google Cloud, Azure, and have it managed for you by the experts, with serverless, pay-as-you-go pricing.

Implementation language

Java

C++

Java, C++

Server operating systems

Linux
OS X

Windows

Not a real database server, but making use of DLLs

Linux

Linux
OS X

for development

Data scheme

schema-free

yes

schema-free

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.

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

only a subset of SQL 99

APIs and other access methods

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

ADO.NET
DAO
ODBC
OLE DB

C++ API
Java API

Java API
JDBC
RESTful HTTP/JSON API

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
Perl
Python
Ruby

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

since Access 2010 using the ACE-engine

Java

Triggers

yes

since Access 2010 using the ACE-engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

none

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

yes

Multi-source replication
Source-replica replication

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

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

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

yes

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

but no files for transaction logging

yes

Snapshots and command logging

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

Users and roles with access to stored procedures

More information provided by the system vendor

Specific characteristics

DataStax Enterprise is scale-out data infrastructure for enterprises that need to...
» more

Competitive advantages

Supporting the following application requirements: Zero downtime - Built on Apache...
» more

Typical application scenarios

Applications that must be massively and linearly scalable with 100% uptime and able...
» more

Key customers

Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
» more

Market metrics

Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
» more

Licensing and pricing models

Annual subscription
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.