DBMS > IBM Db2 Event Store vs. LevelDB vs. Oracle Berkeley DB vs. SpatiaLite

System Properties Comparison IBM Db2 Event Store vs. LevelDB vs. Oracle Berkeley DB vs. SpatiaLite

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Editorial information provided by DB-Engines

Name

Description

Distributed Event Store optimized for Internet of Things use cases

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Widely used in-process key-value store

Spatial extension of SQLite

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

Spatial DBMS

Secondary database models

Relational DBMS

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

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

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Score	1.60
Rank	#149	Overall
	#3	Spatial DBMS

Website

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

github.com/google/leveldb

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

www.gaia-gis.it/fossil/libspatialite/index

Technical documentation

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

github.com/google/leveldb/blob/main/doc/index.md

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

www.gaia-gis.it/gaia-sins/spatialite_topics.html

Developer

IBM

Google

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Alessandro Furieri

Initial release

2017

2011

1994

2008

Current release

2.0

1.23, February 2021

18.1.40, May 2020

5.0.0, August 2020

License

Commercial or Open Source

commercial

free developer edition available

Open Source

BSD

Open Source

commercial license available

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C and C++

C++

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

C++

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

Illumos
Linux
OS X
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

server-less

Data scheme

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.

yes

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

yes

SQL interfaced based on SQLite is available

yes

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

Supported programming languages

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

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

.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

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

none

Source-replica replication

none

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

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

No - written data is immutable

yes

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

with automatic compression on writes

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

fine grained access rights according to SQL-standard

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