The Ultimate Query
Only EsgynDB can support querying and joining data from multiple storage engines and across structured, unstructured and semi-structured data.
select * from struct_table, unstruct_table, semi_struct_table, external_source
The Most Capable
EsgynDB runs the entire official TPC-DS benchmark out-of-the-box and delivers high performance/concurrency running industry-standard benchmarks YCSB and TPC-C.
Expect More From Your Big Data Database
Maturity. Sophisticated cost-based and rules-driven query Optimizer adapts to varied and changing workloads. Dynamic parallel execution engine enables executing a mixed set of queries efficiently.
Transactions to Analytics. Run distributed ACID transactions, reporting, BI and analytics on the same platform and eliminate data copies for different workloads.
SQL Power with NoSQL flexibility. Get the best of both worlds – flexibility and scalability of NoSQL with ease of use and streamlined application access of RDBMS.
Predicate Push Down. Eliminate data movement between compute & storage, and across network.
User Defined Function Framework. Extend functionality of the database by allowing integration of external functions (not necessarily written in SQL) within the same SQL statement, and enable automatic query execution in parallel using the SQL engine to boost performance.
Multi-tenancy. Effectively allocate resources for various workloads within a single database instance.
Security. Sophisticated features – role-based access controls, authentication (LDAP/AD), integration with Kerberos, encryption at multiple levels.
Manageability. Esgyn DBManager – a visual dashboard to monitor & manage all aspects of database.
Disaster Recovery. Deploy across multiple data centers in active/active or active/passive modes.
Deployment. In-cloud or on-premise (Esgyn-certified Big Data appliances are available).
Built on Apache Trafodion. EsgynDB is built on Apache Trafodion and Hadoop
Use Cases for Esgyn-powered Data Lakes
· Eliminate data silos / Enhance EDW effectiveness / Self-serve BI & real-time analytics
· Operational Data Store (ODS)
· Internet of Things (IoT and IIoT)
· Offload data transformation (eliminate ETL and use ELT within the SQL engine)
· Reduce time and effort involved in executing AI / ML algorithms