What's New in Version 17.0 (Revisão #279)

Aqua Data Studio's version 17.0 release adds native support for three very popular Big Data and cloud-based data products: SAP Hana, Google BigQuery, and Apache Spark. Business analysts will value the productivity enhancements offered by our enhanced Excel SQL capabilities, our new Excel import wizard and our new MongoDB UI for JavaScript execution . Database administrators will appreciate the expanded DBA tools coverage to manage more databases along with our expanded Explain Plan support to identify SQL query bottlenecks quickly. 

Business intelligence users will applaud the significant enhancements to our Visual Analytics capabilities. We have introduced nine new charts, greatly strengthened our statistical capabilities by offering Reference Lines, Box plots, and R language integration and have delivered many usability enhancements including text and image support in dashboard, customizable color legend and navigation improvements. 

SAP Hana

Dive into SAP HANA
You can now connect to SAP HANA, an in-memory database and application platform to query and analyze your big data and gain valuable insights. Learn More

APACHE SPARK

Query Spark Clusters
You can now connect to Apache Spark, the blazing fast in-memory large-scale data processing engine. Learn More

MongoJS Query Analyzer

Run MongoDB JavaScript commands
Our new MongoJS Query Analyzer, can now run MongoDB javascript commands and display the results in a tree hierarchy. Use MongoJS pretty print JSON, autocompletion, syntax highlighting and many more features. Learn More

 

VISUAL EXPLAIN PLANS

Explain Plans for 7 More Databases
You can now use Explain Plans in Text format for Amazon Redshift, Greenplum, ParAccel, Teradata Aster, Netezza, PostgreSQL and MySQL to help reduce SQL query bottlenecks. Learn More

 

 

GOOGLE BIGQUERY

Query, Analyze BigQuery Datasets
Connect to Google BigQuery, a cloud-based big data analytical web service to explore your projects, run SQL queries, and use the intuitive visual editors for all your BigQuery datasets. Learn More

expanded DBA tools

DBA Tools for Your Databases
We now support DBA tools for Amazon RedShift, PostgreSQL, Greenplum, Teradata Aster, Netezza, ParAccel, Informix, Sybase IQ, Teradata, and Vertica. Learn More

EXCEL improvements

Excel SQL SELECT using WHERE
We now support MS Excel WHERE, ORDER BY, GROUP BY, HAVING, and JOIN clauses that give you the ability to connect, query, and generate results from the XLS and XLSX files. Learn More

 

Excel Import Wizard
Our new Excel Import tool imports data directly from single or multiple Excel sheets into existing or new database tables.  Learn More

new database versions

More DB Version Support
Connect to Cloudera 5.4, HortonWorks 2.3, MapR with Spark, PostgreSQL 9.4, VoltDB 5.5, and Informix 12. Learn More

More Visual Analytics

Nine New Charts
We now offer nine new charts: Filled Map, Highlight Table, Heatmap, Funnel, Gauge, Horizon, Mekko, Radar, and Sunburst so you can produce the data visualizations you need. 

Reference Lines and Box plot
Our powerful new tool highlights aspects of specific interest in a given data set using the Reference Lines. Customers can quickly and conveniently compare multiple data sets against a central theme. Learn More

Rserve Integration with Visual Analytics
Our new Rserve integration enables customers to analyze statistical computing visually and easily. Learn More

Text and Images in Dashboard
We have significantly enhanced our dashboards by introducing Text and Image objects. These objects make dashboards more visually appealing and enable you to analyze your data easily, along with the charts. Learn More

Customizable Color Legend
Our highly customizable measure color gradient provides sequential and diverging color themes, along with the freedom to divide colors into discrete steps and customize the color gradient range. Learn More

New Date, Date and Time Hierarchy Navigation
Our new date and date and time hierarchical enhancement offers great navigational capabilities to drill down into the data. Learn More