CUBRID
CUBRID is a relational DBMS optimized for online transaction processing (OLTP) that complies with ANSI SQL standards and provides MVCC support, High-Availability (HA) capabilities, and GUI-based tools for DB management/migration. It also provides Oracle/MySQL compatibility and supports a variety of interfaces, including JDBC.
CUBRID provides ease of installation and native GUI-based administration tools for developers' convenience. Multi-threaded, multi-server architecture, native broker middleware, cost-based optimizer, and intensive caching techniques for your OLTP services. Very accurate predictable automatic fail-over built-in technology, based on the CUBRID Heartbeat native engine core. Multi-volume support, automatic volume expansion, and unlimited number and size of databases/ tables/indexes.
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InterBase
Ultrafast, scalable, embeddable SQL database with commercial-grade data security, disaster recovery, and change synchronization. Cross-platform, zero-install, embedded database as a direct-access library. Cross-platform, zero-install, embedded database with database-level and column-level AES and DES encryption. Concurrent applications/client access to the database on Windows with database-level and column-level AES and DES encryption. Ultrafast, scalable, SQL server database for Windows and Linux with commercial-grade data security, disaster recovery and change synchronization. Attacks on databases and loss of data can be costly and lead to loss of customers’ trust (and business), regulatory action, and heavy fines. InterBase provides over-the-wire and at-rest encryption, separate security login, and role-based user security. InterBase maintains full on-disk encryption while adding negligible overhead to database speed and performance.
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Apache Trafodion
Apache Trafodion is a webscale SQL-on-Hadoop solution enabling transactional or operational workloads on Apache Hadoop. Trafodion builds on the scalability, elasticity, and flexibility of Hadoop. Trafodion extends Hadoop to provide guaranteed transactional integrity, enabling new kinds of big data applications to run on Hadoop. Full-functioned ANSI SQL language support. JDBC/ODBC connectivity for Linux/Windows clients. Distributed ACID transaction protection across multiple statements, tables, and rows. Performance improvements for OLTP workloads with compile-time and run-time optimizations. Support for large data sets using a parallel-aware query optimizer. Reuse existing SQL skills and improve developer productivity. Distributed ACID transactions guarantee data consistency across multiple rows and tables. Interoperability with existing tools and applications. Hadoop and Linux distribution neutral. Easy to add to your existing Hadoop infrastructure.
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Apache Spark
Apache Spark™ is a unified analytics engine for large-scale data processing. Apache Spark achieves high performance for both batch and streaming data, using a state-of-the-art DAG scheduler, a query optimizer, and a physical execution engine. Spark offers over 80 high-level operators that make it easy to build parallel apps. And you can use it interactively from the Scala, Python, R, and SQL shells. Spark powers a stack of libraries including SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming. You can combine these libraries seamlessly in the same application. Spark runs on Hadoop, Apache Mesos, Kubernetes, standalone, or in the cloud. It can access diverse data sources. You can run Spark using its standalone cluster mode, on EC2, on Hadoop YARN, on Mesos, or on Kubernetes. Access data in HDFS, Alluxio, Apache Cassandra, Apache HBase, Apache Hive, and hundreds of other data sources.
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