DBMS > IBM Db2 Event Store vs. Microsoft Azure Synapse Analytics vs. NSDb vs. VictoriaMetrics

System Properties Comparison IBM Db2 Event Store vs. Microsoft Azure Synapse Analytics vs. NSDb vs. VictoriaMetrics

Please select another system to include it in the comparison.

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

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

A fast, cost-effective and scalable Time Series DBMS and monitoring solution

Primary database model

Event Store
Time Series DBMS

Relational DBMS

Time Series 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	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	1.32
Rank	#162	Overall
	#14	Time Series DBMS

Website

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

azure.microsoft.com/services/synapse-analytics

nsdb.io

victoriametrics.com

Technical documentation

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

docs.microsoft.com/azure/synapse-analytics

nsdb.io/Architecture

docs.victoriametrics.com
github.com/VictoriaMetrics/VictoriaMetrics/wiki

Developer

IBM

Microsoft

VictoriaMetrics

Initial release

2017

2016

2017

2018

Current release

2.0

v1.91, May 2023

License

Commercial or Open Source

commercial

free developer edition available

commercial

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

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++

Java, Scala

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

hosted

Linux
macOS

FreeBSD
Linux
macOS
OpenBSD

Data scheme

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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

all fields are automatically indexed

SQL

Support of SQL

yes

through the embedded Spark runtime

yes

SQL-like query language

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

gRPC
HTTP REST
WebSocket

Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write

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

Java
Scala

Server-side scripts

Stored procedures

yes

Transact SQL

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

yes

Synchronous 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

Eventual Consistency

Foreign keys

Referential integrity

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

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

Using Apache Lucene

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

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

The vision for Db2
26 February 2019, biplatform.nl

Advancements in streaming data storage, real-time analysis and machine learning
25 July 2019, IBM

IBM Builds New Ultra-Fast Platform for Hoovering Up and Analyzing Data from Anywhere
31 May 2018, Data Center Knowledge

How IBM Is Turning Db2 into an 'AI Database'
3 June 2019, Datanami

Best cloud databases of 2022
4 October 2022, ITPro

provided by Google News

Migrate Microsoft Azure Synapse Analytics to Amazon Redshift using AWS SCT | Amazon Web Services
18 October 2023, AWS Blog

Azure Synapse Runtime for Apache Spark 3.2 End of Support | Azure updates
22 March 2024, Microsoft

Azure Synapse Analytics: Everything you need to know about Microsoft's cloud analytics platform
24 September 2023, DataScientest

Azure Synapse vs. Databricks: Data Platform Comparison 2024
26 March 2024, eWeek

Azure Synapse Link for Cosmos DB: New Analytics Capabilities
10 November 2023, InfoQ.com

provided by Google News

OpenTelemetry Is Too Complicated, VictoriaMetrics Says
1 April 2024, Datanami

KubeCon24: VictoriaMetrics' Simpler Alternative to Prometheus
20 March 2024, The New Stack

Green coding - VictoriaMetrics: The efficiency vs complexity trade-off
15 May 2024, ComputerWeekly.com

How VictoriaMetrics' open source approach led to mass industry adoption
3 May 2024, Tech.eu

VictoriaMetrics Machine Learning takes monitoring to the next level
19 March 2024, businesswire.com

provided by Google News

Share this page