Jethro to deliver Interactive BI service at attractive Hadoop costs. Jethro transparently supports all SQL queries, for thousands of concurrent users analyzing tens of billions of rows. All that with interactive response times measured in seconds.
Hadoop Analytics Platform
• Interactive BI dashboards at Big Data scale
• No manual data engineering
• Seamlessly integrates with existing BI applications and data lake
• Typical Use Cases
• Interactive performance for all types of queries
• Jethro delivers Interactive BI for all types of queries
• Jethro customers can focus on Interactive BI and save on costly busywork
Small (<50 employees), Medium (50 to 1000 Enterprise (>1001 employees)
Jethro is the business intelligence engine for big data. Customers use Jethro to deliver Interactive BI service at attractive Hadoop costs. Jethro transparently supports all SQL queries, for thousands of concurrent users analyzing tens of billions of rows. All that with interactive response times measured in seconds. Customers use Jethro to power their BI apps over Big Data when alternative approaches simply don’t work: extracts are too big, connecting directly to SQL-on-Hadoop is too slow, manual data engineering is too complex, and EDW DBMS’ are too expensive. Jethro’s Cost- Based Optimizer combines three different strategies to deliver interactive performance across all types of queries. Jethro can support 1000s of concurrent users dicing and slicing 10s of billions of up-to-the-minute business data. Jethro delivers such high level of service by computing user queries in real time from Indexes, cubes, and query caches that are automatically maintained and kept current by background services. Jethro does not access the underlying data lake to answer user queries. BI tools send live queries to Jethro via ODBC / JDBC connection. Jethro servers can dynamically scale out to support any level of concurrency. All data—columns, indexes, cubes, cache—is centrally stored in Hadoop, cloud, or NFS, and shared by all Jethro servers. In Jethro for Qlik, queries use indexes to access only the data they need instead of performing a full scan, resulting in much faster response times. Queries can leverage multiple indexes for better performance – the more you drill-down, the faster your query runs.