Netezza aqua data studio3/6/2023 ![]() Those that need a generalpurpose tool to compare and synchronize schema objects and data and to track database sessions, instances and security will find that Aqua Data Additionally, database developers are expected to work seamlessly across disparate DBMSs and integrate their work with source control systems as part of their regular software development cycle.ĭatabase administrators have different levels of responsibilities, and it depends on exactly what they are managing. Today’s database environments are growing exponentially in volume, velocity,Īnd variety, making the database professionals’ roles even more challenging and time-consuming. Current license holders with expired subscriptions can renew their subscriptions for $174.65 USD, which is just 35% of the new license price.Database developers are tasked with creating software applications that include complex business logic and access ever-changing database ecosystems, while database administrators must manage these complex environments that may incorporate a myriad of platforms and versions. The cost of a single-user commercial license for Aqua Data Studio 17 remains $499.00 USD. You can view the complete list of new features and enhancements at. It is available for immediate download at. Supported databases include Amazon Redshift, Greenplum, Teradata Aster, Netezza, PostgreSQL and others.ĭatabase support has been upgraded to include Teradata Aster 6.1, IBM DB2 z/OS 11, Vertica 7.1.2, Cloudera 5.4, Hortonworks 2.3, MapR 5.0, PostgreSQL 9.4, VoltDB 5.5, SQLite 3.8.10.1 and an updated Amazon Redshift driver.Īqua Data Studio Availability and PricingĪqua Data Studio 17.0 is localized in 9 languages and works with Windows, Mac OS X, Linux, Solaris, and the Java Platform. Version 17 offers expanded DBA tools coverage to effortlessly manage more databases and expanded Explain Plan support to quickly identify performance bottlenecks in your SQL queries. In addition, a new Excel import wizard has been added which imports Excel data into existing or new database tables. The new release includes an SQL In-memory database for querying Excel files with full SQL syntax that gives users the ability to connect, query and generate results from Excel files. This new editor provides easy-to-use functionality such as syntax coloring and auto-completion. Version 17 also delivers a new MongoDB JavaScript editor to execute MongoDB commands and display results in a tree hierarchy, grid, and as text. "By adding Google BigQuery, SAP HANA and Apache Spark support, customers can continue testing and migrating to new systems within a seamless interface."ĪquaFold has delivered support for Google BigQuery, SAP HANA and Apache Spark. "Cloud and Hadoop databases continue to gain greater mindshare with our customers," explains Gron. Dashboards have also been enhanced to support text and image objects to more effectively convey your analysis. Filled Maps can now be used to plot geographic data and Horizon charts can be used to visualize large volumes of time series data. Improvements to Aqua Data Studio's visual analytics tool include nine new chart types, which provide richer visualizations and R language integration for data analysis. "We've added R language integration to bridge the gap between adhoc query tasks and on-the-fly analysis." "We have an increasing demand from users to perform advanced analytics on their adhoc queries," says AquaFold's CEO, Niels Gron. This Smart News Release features multimedia. Along with enhanced Excel capabilities, a new MongoDB JavaScript editor, expanded DBA Tools and Explain Plans, and new charts and analytics, version 17 is the most functional release to date. The latest version increases productivity for business analysts, expands database integration for database administrators, and offers richer data insights for business intelligence users. has released Aqua Data Studio 17, a major upgrade to its universal database management and analytics software, allowing users to design and administer the newest class of Big Data and cloud-based databases. ![]()
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