DBMS > IBM Db2 Event Store vs. Oracle Berkeley DB vs. Snowflake vs. VoltDB

System Properties Comparison IBM Db2 Event Store vs. Oracle Berkeley DB vs. Snowflake vs. VoltDB

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Editorial information provided by DB-Engines

Name

Description

Distributed Event Store optimized for Internet of Things use cases

Widely used in-process key-value store

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

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

Event Store
Time Series DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Relational DBMS

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

Score	0.27
Rank	#309	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	2.01
Rank	#126	Overall
	#21	Key-value stores
	#3	Native XML DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

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

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

www.snowflake.com

www.voltdb.com

Technical documentation

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

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

docs.snowflake.net/manuals/index.html

docs.voltdb.com

Developer

IBM

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Snowflake Computing Inc.

VoltDB Inc.

Initial release

2017

1994

2014

2010

Current release

2.0

18.1.40, May 2020

11.3, April 2022

License

Commercial or Open Source

commercial

free developer edition available

Open Source

commercial license available

commercial

Open Source

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

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C and C++

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

Java, C++

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

hosted

Linux
OS X

for development

Data scheme

yes

schema-free

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.

yes

only with the Berkeley DB XML edition

yes

Secondary indexes

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

yes

SQL interfaced based on SQLite is available

yes

only a subset of SQL 99

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

CLI Client
JDBC
ODBC

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

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

JavaScript (Node.js)
Python

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions

Java

Triggers

yes

only for the SQL API

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

Source-replica replication

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

No - written data is immutable

yes

Data access is serialized by the server

Durability

Support for making data persistent

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

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

fine grained access rights according to SQL-standard

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

Users and roles with access to stored procedures

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