About IBM DB2
Finding a good Db2 connector is tough! Use ours for both extracting data from and loading data to.
About Databricks
Extract data from and load data into Databricks to power your advanced analytics, machine learning pipelines, and business intelligence use cases. Do more with your Databricks data.
Popular Use Cases
Bring all your Databricks data to Amazon Redshift
Load your Databricks data to Google BigQuery
ETL all your Databricks data to Snowflake
Move your Databricks data to MySQL
IBM DB2's End Points
IBM Db2 Database
Db2 Database is a relational database management system (RDBMS) optimized for high-performance transactional workloads. As an operational database management system, Db2 Database is not only highly performant and reliable, but it also allows you to derive actionable insights from your operational data. Db2 Database delivers advanced features like in-memory technology, storage optimization, continuous data availability, workload management, and cutting-edge management and development tools. Db2 Database is compatible with Windows, Linux, and Unix.
IBM Db2 on Cloud (IBM Db2 Hosted)
Db2 on Cloud is a fully-managed, SQL-based transactional database that runs on the cloud. One of the defining characteristics of Db2 on Cloud is its high-availability option, which delivers 99.99% uptime (according to IBM). This cloud-based database offers automatic security updates and independently scalable storage and processing, which automatically scales resources up and down based on usage requirements. Available on AWS and IBM Cloud, Db2 on Cloud delivers advanced features for backup and recovery, encryption, and data federation. Through its private networking features, you can also deploy Db2 on Cloud on a private network accessible over a secure VPN. Db2 Hosted is the hosted, unmanaged version of the Db2 on Cloud SQL-based cloud database.
IBM Db2 Warehouse
As a data management system optimized for high-speed read operations, data aggregation, and analysis, IBM Db2 Warehouse has evolved over time to offer a range of advanced analytics and data management features. Db2 Warehouse allows you to combine data from various transactional and operational database systems, and analyze it to find deep insights, patterns, and hidden relationships. Db2 Warehouse supports a range of data types, machine learning algorithms, analytical models. For example, Db2 Warehouse supports relational data, non-relational data, geospatial data, multi-parallel processing, predictive modeling algorithms, in-memory analytical processing, Apache Spark, RStudio, XML data, embedded Spark Analytics engine, and more. Db2 Warehouse runs on-premises, on the private cloud, and on various public clouds as a managed or unmanaged solution.
IBM Db2 Warehouse on Cloud (dashbDB for Analytics)
Db2 Warehouse on Cloud (formerly known as “dashDB for Analytics”) is a fully-managed, highly-scalable, cloud-based data warehouse management system. IBM optimized Db2 Warehouse on Cloud to perform compute-heavy data analytics and machine learning processes at scale. The product offers autonomous cloud services with Db2's autonomous self-tuning processing engine, in addition to its fully-automated database monitoring, uptime monitoring, and operations monitoring. Db2 Warehouse on Cloud also includes capabilities for column-based storage, querying compressed datasets, data skipping, and in-memory processing. Finally, Db2 Warehouse on Cloud delivers in-database geospatial data and machine learning features – including algorithms for ANOVA, Association Rule, k-means, Naïve Bayes, Regression analysis, in-database spatial analytics, support for Esri data types, and it natively includes Python drivers and a Db2 Python integration for Jupyter Notebooks. To access these and other features, you can deploy Db2 Warehouse on Cloud via AWS or IBM Cloud.
IBM Db2 BigSQL (IBM SQL)
Db2 BigSQL (formerly known as “IBM SQL”) is a high-performance SQL data engine on Hadoop featuring a Massively Parallel Processing (MPP) architecture. Also known as “Big SQL,” this highly-scalable data engine offers ease and security while querying data from multiple sources across your enterprise. Big SQL can rapidly query data from the widest variety of sources such as RDBMS, HDFS, WebHDFS, object stores, and NoSQL databases. As a hybrid ANSI-compliant SQL engine, Big SQL is highly performant when running queries on unstructured streaming data. Finally, Big SQL is compatible with the entire suite of Db2 products, in addition to the IBM Integrated Analytics System.
Db2 Event Store
Db2 Event Store is a data management system optimized for storing and analyzing high-speed, high-volume, streaming data. Use-cases for Db2 Event Store include Internet of Things (IoT) networks, financial services systems, telecommunications networks, industrial systems, and online retail business systems. The solution offers high-speed analytics and data capture features that allow you to save and analyze up to 250 billion event records daily using only three server nodes. Db2 Event Store integrates IBM Watson Studio technology to support artificial intelligence and machine learning analyses. The solution was also built on Spark, so it works with Spark SQL, Spark Machine Learning, and other compatible tools. Finally, Db2 Event Store supports Go, ODBC, JDBC, Python, and other languages.
Databricks's End Points
Table of Contents
- Connect Databricks for a single source of truth
- Migrate your Databricks data in minutes
- Integrate.io has the Databricks integrations you need
- How Integrate.io customers grow faster with Databricks data connectors
- Get started analyzing your Databricks data
- Why choose Integrate.io for your Databricks integration?
Connect Databricks for a Single Source of Truth
Databricks unifies your data engineering, data science, and analytics workflows. However, its true value is unlocked when it connects to the broader data ecosystem, such as CRMs, ERPs, SaaS tools, and cloud platforms.
With Integrate.io’s Databricks connector, you can centralize your data, streamline pipelines, and ensure that the insights you generate in Databricks are based on complete, timely information.
Use Integrate.io to:
With Integrate.io’s Databricks connector, you can centralize your data, streamline pipelines, and ensure that the insights you generate in Databricks are based on complete, timely information.
Use Integrate.io to:
- Load structured and semi-structured data into Databricks from APIs, databases, and applications
- Extract clean, transformed data from Databricks into analytics and reporting tools
- Sync Databricks with data warehouses and business systems in real time
Migrate Your Databricks Data in Minutes
Whether you’re building your first Delta Lake table or integrating Databricks into an existing ML pipeline, Integrate.io simplifies the setup. No complex scripting. No hand-coded workflows.
With Integrate.io, you can:
With Integrate.io, you can:
- Create Databricks pipelines via drag-and-drop configuration
- Push large datasets from multiple systems into Databricks quickly and securely
- Transform and model data in-flight before loading into Databricks
- Extract data from Databricks notebooks, jobs, and clusters for use in downstream platforms
Integrate.io Has the Databricks Integrations You Need
From operational data ingestion to machine learning preparation, Integrate.io helps Databricks fit seamlessly into your stack, without writing code.
Popular integration use cases include:
Popular integration use cases include:
- Moving Salesforce or HubSpot data into Databricks for customer modeling
- Pushing ecommerce clickstream data into Databricks for product analytics
- Exporting feature-engineered datasets from Databricks into Snowflake or BigQuery
- Using Databricks as a transformation layer before feeding dashboards in Tableau or Power BI
How Integrate.io Customers Grow Faster with Databricks Data Connectors
Innovation happens faster when Databricks is integrated with all your critical data sources. Machine learning models improve. Analytics are more complete. Decisions become more accurate.
Integrate.io helps you unlock the full potential of Databricks by making data from across your systems available, cleaned, transformed, and ready for use.
Every team benefits from connected Databricks workflows, from marketing to product to finance.
Every team benefits from connected Databricks workflows, from marketing to product to finance.
Get Started Analyzing Your Databricks Data
Whether you're prepping training data, running real-time inference, or visualizing KPIs, the key is unified data. Integrate.io connects Databricks with the platforms where your business operates.
With a few clicks, you can:
With a few clicks, you can:
- Connect Databricks to your warehouse for bi-directional sync
- Send transformed datasets from Databricks to BI tools
- Orchestrate ETL pipelines involving Delta Lake, MLflow, and more
Why Choose Integrate.io for Your Databricks Integration?
Integrate.io is built for modern data workflows, batch or streaming, structured or messy, warehouse or lakehouse.
Key advantages include:
Key advantages include:
- A no-code/low-code interface for rapid integration
- Support for Delta Lake, JDBC, and REST APIs
- Powerful transformation engine with built-in scheduling
- Secure, compliant data handling for enterprise-grade deployments
- Top-tier support and deep documentation
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