DBMS > Bangdb vs. Datastax Enterprise vs. IBM Db2 Event Store vs. Microsoft Access vs. SAP HANA

System Properties Comparison Bangdb vs. Datastax Enterprise vs. IBM Db2 Event Store vs. Microsoft Access vs. SAP HANA

Editorial information provided by DB-Engines

Name

Description

Converged and high performance database for device data, events, time series, document and graph

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.

Distributed Event Store optimized for Internet of Things use cases

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.)

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Document store
Graph DBMS
Time Series DBMS

Wide column store

Event Store
Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	5.80
Rank	#60	Overall
	#4	Wide column stores

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

bangdb.com

www.datastax.com/products/datastax-enterprise

www.ibm.com/products/db2-event-store

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

www.sap.com/products/hana.html

Technical documentation

docs.bangdb.com

docs.datastax.com

www.ibm.com/docs/en/db2-event-store

developer.microsoft.com/en-us/access

help.sap.com/hana

Developer

Sachin Sinha, BangDB

DataStax

IBM

Microsoft

SAP

Initial release

2012

2011

2017

1992

2010

Current release

BangDB 2.0, October 2021

6.8, April 2020

2.0

1902 (16.0.11328.20222), March 2019

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

BSD 3

commercial

free developer edition available

commercial

Bundled with Microsoft Office

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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

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Implementation language

C, C++

Java

C and C++

C++

Server operating systems

Linux

Linux
OS X

Linux

Linux, macOS, Windows for the developer addition

Windows

Not a real database server, but making use of DLLs

Appliance or cloud-service

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

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

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

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

yes

through the embedded Spark runtime

yes

but not compliant to any SQL standard

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

ADO.NET
DAO
ODBC
OLE DB

JDBC
ODBC

Supported programming languages

C
C#
C++
Java
Python

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

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

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

Server-side scripts

Stored procedures

yes

since Access 2010 using the ACE-engine

SQLScript, R

Triggers

yes, Notifications (with Streaming only)

yes

since Access 2010 using the ACE-engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Sharding

no "single point of failure"

Sharding

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

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

Active-active shard replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Immediate Consistency
Tunable Consistency

consistency level can be individually decided with each write operation

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomicity and isolation are supported for single operations

ACID

but no files for transaction logging

ACID

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

No - written data is immutable

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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, run db with in-memory only mode

yes

User concepts

Access control

yes (enterprise version only)

Access rights for users can be defined per object

fine grained access rights according to SQL-standard

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

yes

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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