Tibero is a relational database management system developed by TmaxSoft. It is one of the most widely used DBMS among companies and public sectors in South Korea. It is currently owned/managed by TmaxData, an affiliate company of TmaxSoft.


Tibero was first released in June 2003 by TmaxSoft. Tibero 4 was the first version to introduce Tibero Active Cluster (TAC) for distributed database clustering, and this feature has carried onto newer versions since then. Tibero 6, its latest version as of Nov 2019, was released in 2015.

Storage Model

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.

Isolation Levels


Tibero claims to ensure Serializable isolation level


B+Tree BitMap

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.

Storage Architecture


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.

Data Model


Storage Organization


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.

Parallel Execution

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.

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Tech Docs




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Supported languages

C, C++, Java, PL/SQL, SQL

Compatible With

Oracle RDBMS

Operating Systems

AIX, HP-UX, Linux, Solaris, Windows