Multiple data sources have become increasingly common. Business user need to mix and match data from many internal and cloud sources of different types and vendors. And they need to get immediate results.
Querona provides a set of connectors to more than 100 types of data sources and makes them connected in a few clicks. No matter what kind and how many sources you have, you get secure and real-time data access using the standard SQL dialect.
When dashboards slow down, you can retarget queries to another execution engine. Just indicate where to prepare data extract and let Querona do the rest. Leverage the built-in big data engine Apache Spark 2 or use external data processing engines like Microsoft SQL Server, Azure SQL Data Warehouse, Apache Spark on Hadoop or a combination of 15 supported data engines. Improve reporting performance by enabling caching and preaggregation. Eliminate connectivity bottlenecks, data processing overheads and benefit from columnar data processing instantly.
Marketing teams are using Power BI, finance QlikView and sales teams are allergic to anything but Excel? We’re fine with that. Any presentation tool can be used and no drivers are needed on user’s machines. Querona fully emulates Microsoft SQL Server, lets you build a central data hub, and present dashboards in any tool that supports standard Transact-SQL. Just connect to Querona using Windows Integrated authentication or standard authentication mechanism as if it was SQL Server.
Let your users use what they are familiar with. They will love that flexibility.
Querona is a virtual database that allows pass-through access to all corporate data sources from one place – now reporting is simpler. There is one place to find all data sources.
Querona accepts standard SQL (compatible with SQL Server) and translates queries to run them on other databases. You can run full SQL on any data source, no matter if it is SQL Server, Oracle or a cloud applications like SalesForce or Marketo. Data exploration, data preparation and report prototyping are available instantly.
Querona combines traditional Business Intelligence with Big Data processing. The Logical Data Warehouse may now grow following the increase of the data volume in the future. You can build a future-proof Data Lake.
The integrated Apache Spark engine makes it possible to start processing Big Data just 5 minutes after setting up Querona. Migration to a Hadoop cluster on-premise or in the cloud is just a configuration change. The Querona price does not depend on the data volumes or the Spark cluster size.
Data preparation for reporting always depends on building ETL processes that load data to a data warehouse. The Logical Data Warehousing architecture in Querona simplifies the process just by simply selecting which source tables should be cached, when and where. Data analysts may prepare reports faster and benefit from rapid prototyping.
Querona additionally enables data loading to Hadoop clusters. No need to hire Hadoop experts and wait several weeks for a project that uploads corporate data to a Data Lake.
Querona accelerates queries using dynamic query rewriting. It is now possible to build an efficient cube and cache pre-aggregated views on any SQL database. Existing dashboards may be instantly accelerated by defining pre-aggregates. Now a report that was querying 100M rows would process just a few thousand rows in a cached preaggregate and therefore a slow report will show with no delay.
Internally Querona processes data in columnar format. Direct integration with Apache Spark and an end-to-end columnar processing enables unmatched performance.
Querona enables secure and real-time access to all data sources. All data sources may be queried using the SQL dialect compatible with SQL Server. Now users can get live data no matter where it is stored. Querona supports predicate push-down, join push-down and the best execution plan is selected by our cost-based optimizer.
Of course some data sources or OLTP databases are too slow or too busy to be queried live. Querona solves the issue by caching data on a selected SQL database or on Apache Spark. Caching supports partitioning and high availability refresh to enable fast query execution, with non-stop access to the cache.
Querona emulates SQL Server and exposes a SQL Server compatible interface. Any SQL Server driver (ODBC, JDBC, ADO.NET) can connect and execute queries without the need to install vendor specific drivers.
This feature allows expansion of Business Intelligence to all users in the company. Secure, cached or live data access to all corporate data sources may be possible even from Excel.
Querona supports Windows Integrated authentication and fully integrates with Active Directory. Over 50 types of access rights may be assigned at multiple levels and are enforced in one place over all on-premise and cloud data sources.
Role based security, column data access, row data access and dynamic role based data masking enable unified access to any data source. A cloud data warehouse or a Hadoop cluster may be easily integrated and exposed to users without risk.
Querona data modeling interface is fully web-based and designed for self-service activities. Business users, business analysts, and data scientists can easily find and query any data source needed. With Querona a company may build a central reporting data model. Now a business user can connect to Querona using Excel and retrieve data from the reporting model directly.
Data sources, tables or even columns may be tagged with business terms. With Querona it is easy to find any tables from any data sources that contain customer details. Querona users may collaborate and build a corporate data hub.
Querona integrates cloud data warehouses into the corporate network. Data from on-premise and cloud data sources may be easily uploaded to a data warehouse hosted in the cloud. Now offloading to Azure SQL Data Warehouse or HDInsight is simplified and some activities may be delegated to business users or data scientists.
Querona has a high-availability integration with Hadoop and Apache Spark using Zookeeper. Integration of a Hadoop cluster is safe and reliable.