1. Impala :
Impala is a query engine that runs on Hadoop. It provides high-performance, low-latency SQL queries on data stored in Hadoop. It is an open-source software. It supports in-memory data processing. It is pioneering the use of the Parquet file format, a columnar storage layout that is optimized for large-scale queries typical in data warehouse scenarios.
2. dBASE :
dBASE was one of the most successful database management systems for microcomputers. It was the first commercially successful database system for personal computers. It is used for creating and manipulating relational databases (RDBMS). DBASE uses procedural functions and commands similar to the BASIC language. It uses simple commands for data manipulation like USE, GO TOP, and more.
Difference between Impala and dBASE :
| S.NO. | Impala | dBASE |
|---|---|---|
| 1. | It was developed by Cloudera. | It was developed by Ashton Tate. |
| 2. | It was launched in 2013. | It was launched in 1979. |
| 3. | Run over operating system is Linux. | Run over operating systems are DOS (dBASE Classic) and Windows (dBASE Pro). |
| 4. | It is an open-source software. | It is a commercial software. |
| 5. | JDBC and ODBC are the APIs and access methods used in Impala. | No APIs and access method are used in dBASE. |
| 6. | All programming languages supporting JDBC/ODBC are supported by Impala. | dBASE proprietary IDE is supported by dBASE. |
| 7. | Impala uses Sharding partitioning method for storing different data on different nodes. | dBASE does not use any partitioning method. |
| 8. | No concept of referential integrity and no Foreign keys in Impala. | Referential integrity is used in dBASE. |
| 9. | It uses Selectable Replication Factor for redundantly storing data on multiple nodes. | It does not use any replication method. |
| 10. | There are no transaction concepts in Impala. | There are no transaction concepts for dBASE internal data, but IDE does support transactions when accessing external DBMS. |