DBMS > IBM Db2 Event Store vs. InfinityDB vs. Kingbase vs. Lovefield

System Properties Comparison IBM Db2 Event Store vs. InfinityDB vs. Kingbase vs. Lovefield

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Editorial information provided by DB-Engines

Name

Description

Distributed Event Store optimized for Internet of Things use cases

A Java embedded Key-Value Store which extends the Java Map interface

An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.

Embeddable relational database for web apps written in pure JavaScript

Primary database model

Event Store
Time Series DBMS

Key-value store

Relational DBMS

Secondary database models

Document store
Spatial 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	0.08
Rank	#365	Overall
	#55	Key-value stores

Score	0.50
Rank	#257	Overall
	#119	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Website

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

boilerbay.com

www.kingbase.com.cn

google.github.io/lovefield

Technical documentation

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

boilerbay.com/infinitydb/manual

github.com/google/lovefield/blob/master/docs/spec_index.md

Developer

IBM

Boiler Bay Inc.

BeiJing KINGBASE Information technologies inc.

Google

Initial release

2017

2002

1999

2014

Current release

2.0

4.0

V8.0, August 2021

2.1.12, February 2017

License

Commercial or Open Source

commercial

free developer edition available

commercial

Open Source

Apache 2.0

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.

Implementation language

C and C++

Java

C and Java

JavaScript

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

All OS with a Java VM

Linux
Windows

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Data scheme

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

yes

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

Secondary indexes

manual creation possible, using inversions based on multi-value capability

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

Standard with numerous extensions

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT

Supported programming languages

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

Java

.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

JavaScript

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning (by range, list and hash) and vertical partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

none

yes

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

READ-COMMITTED or SERIALIZED

Immediate Consistency

Foreign keys

Referential integrity

manual creation possible, using inversions based on multi-value capability

yes

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

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

yes, by using IndexedDB or the cloud service Firebase Realtime Database

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

User concepts

Access control

fine grained access rights according to SQL-standard

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