DBMS > IBM Db2 Event Store vs. Microsoft Azure Synapse Analytics vs. Pinecone vs. SpatiaLite

System Properties Comparison IBM Db2 Event Store vs. Microsoft Azure Synapse Analytics vs. Pinecone vs. SpatiaLite

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Editorial information provided by DB-Engines

Name

Description

Distributed Event Store optimized for Internet of Things use cases

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

A managed, cloud-native vector database

Spatial extension of SQLite

Primary database model

Event Store
Time Series DBMS

Relational DBMS

Vector DBMS

Spatial DBMS

Secondary database models

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	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	3.23
Rank	#92	Overall
	#2	Vector DBMS

Score	1.63
Rank	#146	Overall
	#3	Spatial DBMS

Website

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

azure.microsoft.com/services/synapse-analytics

www.pinecone.io

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

Technical documentation

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

docs.microsoft.com/azure/synapse-analytics

docs.pinecone.io/docs/overview

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

Developer

IBM

Microsoft

Pinecone Systems, Inc

Alessandro Furieri

Initial release

2017

2016

2019

2008

Current release

2.0

5.0.0, August 2020

License

Commercial or Open Source

commercial

free developer edition available

commercial

Open Source

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

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C and C++

C++

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

hosted

server-less

Data scheme

yes

Typing

predefined data types such as float or date

yes

String, Number, Boolean

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.

Secondary indexes

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

yes

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

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

C#
Java
PHP

Python

Server-side scripts

Stored procedures

yes

Transact SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

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

Foreign keys

Referential integrity

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

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

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

yes

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More resources

DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

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Spatial database management systems
6 April 2021, Matthias Gelbmann

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