DBMS > IBM Db2 Event Store vs. Lovefield vs. Machbase Neo vs. Microsoft SQL Server vs. SAP IQ

System Properties Comparison IBM Db2 Event Store vs. Lovefield vs. Machbase Neo vs. Microsoft SQL Server vs. SAP IQ

Editorial information provided by DB-Engines

Name

Description

Distributed Event Store optimized for Internet of Things use cases

Embeddable relational database for web apps written in pure JavaScript

TimeSeries DBMS for AIoT and BigData

Microsofts flagship relational DBMS

Columnar RDBMS optimized for Big Data analytics

Primary database model

Event Store
Time Series DBMS

Relational DBMS

Time Series DBMS

Relational DBMS

column-oriented

Secondary database models

Document store
Graph DBMS
Spatial 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	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	0.12
Rank	#339	Overall
	#30	Time Series DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	2.75
Rank	#104	Overall
	#53	Relational DBMS

Website

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

google.github.io/lovefield

machbase.com

www.microsoft.com/en-us/sql-server

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

Technical documentation

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

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

machbase.com/dbms

learn.microsoft.com/en-US/sql/sql-server

help.sap.com/docs/SAP_IQ

Developer

IBM

Google

Machbase

Microsoft

SAP, formerly Sybase

Initial release

2017

2014

2013

1989

1994

Current release

2.0

2.1.12, February 2017

V8.0, August 2023

SQL Server 2022, November 2022

16.1 SPS04, April 2019

License

Commercial or Open Source

commercial

free developer edition available

Open Source

Apache 2.0

commercial

free test version available

commercial

restricted free version is available

commercial

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++

JavaScript

C++

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

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

tested with Chrome, Firefox, IE, Safari

Linux
macOS
Windows

Linux
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

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

Secondary indexes

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

SQL-like query language

via JavaScript builder pattern

SQL-like query language

yes

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

ADO.NET
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

JavaScript

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

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

C
C#
C++
Java
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

shared disk or shared nothing architectures with SAP IQ Multiplexer

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

none

selectable replication factor

yes, but depending on the SQL-Server Edition

SAP/Sybase Replication Server

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

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, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

yes

volatile and lookup table

yes

User concepts

Access control

fine grained access rights according to SQL-standard

simple password-based access control

fine grained access rights according to SQL-standard

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