A computer implemented method for unified query processing, the method comprising: providing a unified table architecture of an in-memory database, the unified table architecture including a multi-level storage architecture having a first level storage structure (402,602) to store incoming data requests in a logical row format as data records in a write-optimized manner, a second level storage structure (404,604) to encode and store the data records in a logical column format, and a read-optimized main store (406,606) to compress and store the encoded data records for long-term storage, wherein the second level storage structure (404,604) employs dictionary encoding in an unsorted dictionary, wherein values within a column in the main store (406,606) are represented via a position in a sorted dictionary for optimal compression and stored in a bit-packed manner; receiving an SQL query by a common query execution engine connected with the unified table architecture, the query specifying a data record; mapping the query to a data flow graph in a calculation model, the data flow graph comprising source nodes representing persistent table structures and inner nodes reflecting logical operators; providing, by an engine layer, physical operators, wherein the physical operators include relational operators, OLAP operators, operators of an internal runtime language, text operators, and graph operators, wherein the relational operators include equi-join; mapping fragments of the data flow graph to one or more of the physical operators provided by the engine layer; performing, by the common query execution engine, a look-up for the data record based on the query at the first level storage structure (402,602); and if the data record is not present at the first level storage structure (402,602), performing, by the common query execution engine, separate look-ups in each of the second level storage structure (404,604) and the main store (406,606). providing a unified table architecture of an in-memory database, the unified table architecture including a multi-level storage architecture having a first level storage structure (402,602) to store incoming data requests in a logical row format as data records in a write-optimized manner, a second level storage structure (404,604) to encode and store the data records in a logical column format, and a read-optimized main store (406,606) to compress and store the encoded data records for long-term storage, wherein the second level storage structure (404,604) employs dictionary encoding in an unsorted dictionary, wherein values within a column in the main store (406,606) are represented via a position in a sorted dictionary for optimal compression and stored in a bit-packed manner; a first level storage structure (402,602) to store incoming data requests in a logical row format as data records in a write-optimized manner, a second level storage structure (404,604) to encode and store the data records in a logical column format, and a read-optimized main store (406,606) to compress and store the encoded data records for long-term storage, wherein the second level storage structure (404,604) employs dictionary encoding in an unsorted dictionary, wherein values within a column in the main store (406,606) are represented via a position in a sorted dictionary for optimal compression and stored in a bit-packed manner; receiving an SQL query by a common query execution engine connected with the unified table architecture, the query specifying a data record; mapping the query to a data flow graph in a calculation model, the data flow graph comprising source nodes representing persistent table structures and inner nodes reflecting logical operators; providing, by an engine layer, physical operators, wherein the physical operators include relational operators, OLAP operators, operators of an internal runtime language, text operators, and graph operators, wherein the relational operators include equi-join; mapping fragments of the data flow graph to one or more of the physical operators provided by the engine layer; performing, by the common query execution engine, a look-up for the data record based on the query at the first level storage structure (402,602); and if the data record is not present at the first level storage structure (402,602), performing, by the common query execution engine, separate look-ups in each of the second level storage structure (404,604) and the main store (406,606).