As a hybrid data approach, the IBM Db2 suite of products integrates all aspects of data management and analytics – for both relational and object-oriented data models – within a single, highly-compatible family of tools and technologies. IBM Db2 offers RDBMS, data warehousing, and data engine tools for cloud-based systems and on-premises systems. Plus, with Integrate.io’s native Db2 connector, you can instantly connect to any piece of the IBM Db2 toolkit to leverage Db2's capacity to share, access, and analyze both structured and unstructured data – no matter where it is located.
CleverTap allows users to analyze both business analytics and user engagement on one single platform. This gives CleverTap users insight into app user activity, allowing them to see where users have taken action, what information they find compelling, and where they drop off. This information can help businesses improve their long-term strategies, running clever campaigns, sending personalized push notifications, and creating both triggered and scheduled marketing campaigns.
Bring all your CleverTap data to Amazon Redshift
Load your CleverTap data to Google BigQuery
ETL all your CleverTap data to Snowflake
Move your CleverTap data to MySQL
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.
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.
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.
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.
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 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.
Gather data about cohorts, or groups of users who have taken certain actions in your app. Measure retention, engagement and a variety of business metrics for a cohort of users on a daily, weekly and monthly basis.
Retrieve data about a customer’s journeys through your funnel. This data contains the customer’s timeline from start to finish - including how many steps in the funnel the customer completed during that time - which can be used to identify which steps during a funnel most commonly include specific events, such as losing a customer.
Gather segmentation data that is filtered based on an array of properties, such as past behavior and profile attributes. Then, use that filtered data to get deeper, more detailed analytics into your product performance or to reach users with personalized, contextualized messaging.
Track customer engagement data, including a customer’s name and email address, as well as the date and time they last accessed your product. This allows you to run predictive analytics, which can show when engagement will likely drop or increase based on historical engagement data.
Use CleverTap’s APIs for events, user profiles, dashboard counts and push notifications to filter your data and gather key insights.
Get retention data for a specific cohort of customers by tracking signups and other relevant events during a specified date range. Then, feed that data into your analytics to provide a more comprehensive view of your retention trends over time.