DBMS > Apache Cassandra vs. BigchainDB vs. IBM Db2 Event Store vs. Oracle Berkeley DB

System Properties Comparison Apache Cassandra vs. BigchainDB vs. IBM Db2 Event Store vs. Oracle Berkeley DB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

Distributed Event Store optimized for Internet of Things use cases

Widely used in-process key-value store

Primary database model

Wide column store

Document store

Event Store
Time Series DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Secondary database models

Vector DBMS

starting with release V5

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

Score	98.94
Rank	#11	Overall
	#1	Wide column stores

Score	0.76
Rank	#216	Overall
	#36	Document stores

Score	0.18
Rank	#315	Overall
	#2	Event Stores
	#26	Time Series DBMS

Score	1.88
Rank	#130	Overall
	#23	Key-value stores
	#3	Native XML DBMS

Website

cassandra.apache.org

www.bigchaindb.com

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

www.oracle.com/database/technologies/related/berkeleydb.html

Technical documentation

cassandra.apache.org/doc/latest

bigchaindb.readthedocs.io/en/latest

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

docs.oracle.com/cd/E17076_05/html/index.html

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

IBM

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Initial release

2008

2016

2017

1994

Current release

5.0-rc1, July 2024

2.0

18.1.40, May 2020

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

AGPL v3

commercial

free developer edition available

Open Source

commercial license available

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.

Astra DB: Multi-cloud DBaaS built on Apache Cassandra.

Implementation language

Java

Python

C and C++

C, Java, C++ (depending on the Berkeley DB edition)

Server operating systems

BSD
Linux
OS X
Windows

Linux

Linux, macOS, Windows for the developer addition

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Data scheme

schema-free

yes

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

only with the Berkeley DB XML edition

Secondary indexes

restricted

only equality queries, not always the best performing solution

yes

SQL

Support of SQL

SQL-like SELECT, DML and DDL statements (CQL)

yes

through the embedded Spark runtime

yes

SQL interfaced based on SQLite is available

APIs and other access methods

Proprietary protocol

CQL (Cassandra Query Language, an SQL-like language)
Thrift

CLI Client
RESTful HTTP API

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

Supported programming languages

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

Go
Haskell
Java
JavaScript
Python
Ruby

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

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

Server-side scripts

Stored procedures

yes

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Representation of geographical distribution of servers is possible

selectable replication factor

Active-active shard 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

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomicity and isolation are supported for single operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

Durability

Support for making data persistent

yes

yes,with MongoDB ord RethinkDB

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

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

yes

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

Apache Cassandra is the leading NoSQL, distributed database management system, well...
» more

Competitive advantages

No single point of failure ensures 100% availability . Operational simplicity for...
» more

Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
» more

Key customers

Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
» more

Market metrics

Apache Cassandra is used by 40% of the Fortune 100.
» more

Licensing and pricing models

Apache licenseÂ Pricing for commercial distributions provided by DataStax and available...
» more

News

Glean and DataStax Partner to Help Developers Harness Powerful Enterprise Search
23 September 2024

DataStax Named a Leader in The Forrester Wave™: Vector Databases, Q3 2024
23 September 2024

How to Build a Notion Clone with Astra DB and Mongoose
20 September 2024

How to Monitor DataStax-Powered RAG Applications with Fiddler
19 September 2024

How Knowledge Graph RAG Boosts LLM Results
18 September 2024

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.