About MS SQL
Microsoft SQL Server (MS SQL) is a relational database management system (RDBMS) developed by Microsoft that supports transactional processing, analytics applications, business intelligence, and other tasks. The platform stores and retrieves data from applications on your computer or another system in your network.
About Amazon Kinesis
Amazon Kinesis is a powerful analytics solution that overcomes the batch-processing challenges of Hadoop — and similar solutions — which don't allow real-time precision in decision-making because they can't rapidly process high volumes of streaming data. With its ability to process hundreds of terabytes of streaming data per hour, Kinesis allows you to develop apps that rely on real-time data to fuel AI analytics, machine learning insights, and other applications. Kineses enables instant responses by eliminating the delay associated with batch processing.
Popular Use Cases
Bring all your Amazon Kinesis data to Amazon Redshift
Load your Amazon Kinesis data to Google BigQuery
ETL all your Amazon Kinesis data to Snowflake
Move your Amazon Kinesis data to MySQL
MS SQL's End Points
Table of Contents
- 5 Facts About Integrating Microsoft SQL Server Data
- Connect MS SQL Data to a warehouse for a single source of truth
- ETL data from SQL Server in minutes
- Integrate.io has the SQL Server data integrations you need
- How Integrate.io customers power growth with its Microsoft SQL Server connector
- Get started moving data in minutes
- Why choose Integrate.io for MS SQL Server data integration?
- Get started on Microsoft SQL Server data integration
- Explore our Microsoft SQL Server ETL resources
- Check out our latest Microsoft SQL Server-related articles
5 Facts About Integrating Microsoft SQL Server Data
- Microsoft SQL Server is a relational database management system that supports transaction processing, analytics applications, business intelligence, and other tasks.
- Use it to store and retrieve data from other applications that run on the same computer or another system in your network.
- Moving data to and from Microsoft SQL Server typically involves advanced coding and data engineering, proving difficult for many organizations.
- Integrate.io supports SQL Server data integration with its native bi-directional connector that ETLs data to/from the relational database management system.
- Use Integrate.io's connector to integrate SQL Server data in a jargon-free environment.
Connect MS SQL Data to a Warehouse for a Single Source of Truth
Integrating Microsoft SQL Server data to a supported target system like a data warehouse can provide you with a single source of truth for all your marketing data. While MS SQL can handle numerical and binary data types (such as .xml) used for marketing processes, you might want to move this data to a warehouse and have a single reference point for all the marketing information in your business systems. Integrate.io helps you achieve this goal by transferring MS SQL data to a warehouse via an integration process called Extract, Transform, and Load (ETL).
- ETLing SQL Server to a supported warehouse provides a 360-degree overview of customer, campaign, and marketing workflow data.
- Run marketing data through BI tools after moving it to a warehouse and generate intelligence from analysis services for better decision-making.
- View marketing metrics and key performance indicators (KPIs) on dashboards, heatmaps, and other reporting services and share these insights with marketing team members.
Manual ETL might involve complicated processes such as authentication, scripting, permissions, stored procedures, validation, run packages, database engines, SQL statements, file systems, connection strings, data flows, and run time. Integrate.io's range of connectors automates and optimizes the ETL process, allowing you to generate business insights without hiring additional data engineers or building data pipelines. Schedule an intro call
now to learn more!
ETL Data From SQL Server in Minutes
ETLing data from SQL Server to a target system with Integrate.io frees up time and resources for your hard-working data team. Integrate.io's SQL Server data tools move data to a supported warehouse, which can take as little as a few minutes. The no-code data pipeline platform:
- Extracts data from the SQL Server database management system and places it in a staging area.
- Transforms SQL Server data into the correct format for data warehousing and business intelligence. The platform can also improve data quality, helping you comply with data governance guidelines in your industry or region.
- Loads the newly-transformed SQL Server data into a supported warehouse of your choice. Push this data through BI tools like Tableau, Looker, and Microsoft Power BI for incredible insights!
Alternatively, ETL data from disparate sources to Microsoft SQL Server with Integrate.io's bi-directional connector. That can ensure the correct data reaches MS SQL for storage and speed benefits. Integrate.io has a simple philosophy: make data integration easier. Set up an ETL trial meeting
and learn how Integrate.io's MS SQL connection makes life easier for your data team.
Integrate.io Has the SQL Server Data Integrations You Need
Integrate.io's Microsoft SQL Server connection moves data to and from the relational database management system on your terms. No longer will you have to build data pipelines from scratch for data to reach your desired destination!
Examples of Integrate.io Microsoft SQL Server data integrations
View more Microsoft SQL Server integrations on Integrate.io
Integrate.io ETLs data to/from MS SQL with its simple connection managers. Try Integrate.io yourself
for 14 days.
How Integrate.io Customers Power Growth With Its Microsoft SQL Server Connector
Integrate.io's customers receive multiple benefits when ETLing MS SQL Server data via its native connector:
- Streamlined workflows automate SQL Server data integration by preparing and managing data sets, removing the heavy lifting for data teams. That can be easier than using SQL Server Integration Services (SSIS), SSIS catalogs, SQL server agents, SSISDB, and different instances of SQL Server.
- Integrate.io's SQL Server connector removes data silos in organizations by transferring data from isolated locations and legacy systems to a central repository. That improves performance and productivity for customers.
- Pre-built ETL pipelines remove the possibility of human error when extracting, transforming, and loading data to a target system. Integrate.io can improve data quality and help customers achieve their data integration objectives.
Get Started Moving Data in Minutes
Are you ready to ETL SQL Server data? Just enter a few details on a form and talk to an expert
about your data integration project deployment. Integrate.io provides support and guidance for your data team, removing the pain points of extracting, transforming, and loading data.
Why Choose Integrate.io for MS SQL Server Data Integration?
Change Data Capture
As well as ETL, Integrate.io facilitates super-fast change data capture (CDC), allowing you to identify database changes in real or near-real time. Eliminate bulk load updating by streaming data to your target destination.
REST API Connector
Now you can create your own data connector if you don't see one listed on Integrate.io. Pull data from nearly any data source with a REST API!
Integrate.io has an incredible range of pre-built connectors for sources and destinations. These connectors move data to/from Salesforce, Oracle Database, Amazon Redshift (AWS), Azure Synapse Analytics, Google Analytics, Google Cloud Spanner, and more.
Get Started on Microsoft SQL Server Data Integration
Integrate.io's Microsoft SQL Server data connector is available out of the box and ready for you to use! Sign up for an ETL trial set-up meeting
today and start your MS SQL data integration journey.
Explore Our Microsoft SQL Server ETL Resources
Here are some extra resources for SQL Server data integration:
Amazon Kinesis's End Points
Amazon Kinesis Video Streams
Amazon Kineses Video Streams allow you to safely ingest streaming video data from millions of linked devices into AWS for machine learning, analytical, and other processing purposes. The platform then encrypts, stores, and indexes the video data so you can access video with simple APIs, play live video streams, and offer on-demand playback. When incorporating this technology with Amazon Rekognition Video, TensorFlow, ApacheMxNet, and OpenCV, Amazon Kineses Video Streams makes it possible to build video analytics and computer vision processes into your applications.
Amazon Kinesis Data Streams
By capturing, processing, and storing data streams, Amazon Kinesis offers a real-time data streaming solution to ingest large amounts of information from hundreds of thousands — even millions — of sources at the gigabytes-per-second scale. The massive scalability of this solution lets you capture and produce immediate analytics on data pertaining to financial transactions, database event streams, location tracking data, clickstreams, social media activity, and more. Since the availability of streaming data happens in milliseconds, the platform enables real-time analytics of this information for instant detection of anomalies, dynamic price adjustments, precise dashboard metrics, and more.
Amazon Kinesis Data Firehose
Amazon Kinesis Data Firehose provides a simple and durable way to pull your streaming data into data warehouses, data lakes, and analytics solutions. Due to its compatibility with Splunk, Amazon Redshift, Amazon S3, and Amazon Elasticsearch Service, Kinesis Data Firehose empowers real-time data analytics for the dashboarding and BI tools you've come to trust. Fully managed and automatically scaling, you can use Firehose to encrypt, batch, transform, and compress your information before ingestion to boost security and save on disk space.
Amazon Kinesis Data Analytics
Amazon Kinesis Data Analytics helps users without programming knowledge to analyze data streams with SQL or Java. For team members who know SQL, an SQL editor and templates are available for creating streaming applications or querying streaming data. Meanwhile, those with Java knowledge can develop more nuanced streaming applications that perform real-time data transformations and analytical processes.