Tibero stores data files on one or more non-volatile storages. However, in 2008 TmaxSoft released its own in-memory DBMS called Tibero MMDB. In 2012, the company has made an interview that it is currently considering amalgamating the original disk-oriented product with its in-memory DBMS in the future.
Tibero uses B-Trees to create indexes. It also supports organizing tables with clustered indexes on primary keys. Searching on indexes can be done with single attributes or on a range. An index can be created and searched on composite key from multiple attributes. BitMap Indexing is supported for OLAP data warehouses.
Virtual Views Materialized Views
Tibero supports virtual views. It uses materialized views to optimize queries.
Nested Loop Join Hash Join Sort-Merge Join
Tibero supports Hash Join, Nested-Loop Join, and Sort-Merge Join. The query optimizer decides the order of join as well as the type of join to execute the given query. For joins on large data, the query optimizer performs star transformation.
Multi-version Concurrency Control (MVCC)
Tibero uses Multi-version Concurrency Control. To manage Write-Write conflicts, it uses granulated locks on each row, which is Tibero's smallest unit of data. Tibero's background process runs a deadlock detection.
At a physical level, Tibero stores a control file that acts as a directory to keep track of all data files in the database. The data files each belong to a tablespace which refers to a specific table/index. At a logical level, data files are organized as a collection of blocks within a tablespace.
N-ary Storage Model (Row/Record)
Tibero stores table rows in a disk block until the block's free space reaches a percentage below a configurable parameter. Large objects are stored in multiple blocks unless the parameter is configured to be sufficiently large.
Intra-Operator (Horizontal) Inter-Operator (Vertical)
Tibero uses both intra-operator and inter-operator simultaneously for parallel execution. The query coordinator allocates worker threads to perform intra-operator parallelism. The number of worker threads allocated depends on a configurable parameter. These worker threads form a producer set. At the same time, another collection of worker threads called a consumer set is created. The producer set delivers rows to the consumer set to process the next execution plan simultaneously for inter-operator parallelism. The maximum number of execution plans run simultaneously in inter-operator parallelism is two.
http://www.tmaxsoft.com/products/tibero/
https://technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html
TmaxSoft/TmaxData
2003
AIX, HP-UX, Linux, Solaris, Windows