Hana Architecture Overview

“HANA” mean High Performance Analytic Appliance is a combination of hardware and

software platform.

SAP HANA Database is Main-Memory centric data management platform. SAP HANA

Database runs on SUSE Linux Enterprises Server and builds on C++ Language.

SAP HANA Database can be distributed to multiple machines.

HANA Features

Few of the important HANA features are listed below:

1. In-memory database- All operations read and write happen in memory
2. Column stores- Enable massive data compression, partitioning and act as secondary indexes.
3. Parallelism- Uses massive parallel processing across CPU’s
4. Projections- choosing only the column we want to query on and running them in memory
5. Dynamic Aggregation- no need of aggregates. Aggregation on the fly (ex. totals calculated during runtime thereby clearing up most of the space)
6. Active and passive storage- only put mostly used data in active memory
7. Real time analysis- Real time Replication (SLT)
8. SQL Script- have complex calculations to database which is not possible in regular database.

HANA Advantages

SAP HANA Advantages are as mentioned below –

1. SAP HANA is useful as it’s very fast due to all data loaded in-Memory and no need to load
2. data from disk.
3. SAP HANA can be used for the purpose of OLAP (On-line analytic) and OLTP (On-Line
4. Transaction) on a single database.
5. SAP HANA Database consists of a set of in-memory processing engines. Calculation engine is
6. main in-memory Processing engines in SAP HANA. It works with other processing engine like
7. Relational database Engine (Row and Column engine), OLAP Engine, etc.
8. Relational database table resides in column or row store.

Comparison between Row storage and column storage

There are two storage types for SAP HANA table.

1. Row type storage (For Row Table).
2. Column type storage (For Column Table).

Text data and Graph data resides in Text Engine and Graph Engine respectively. There are

some more engines in SAP HANA Database. The data is allowed to store in these engines as

long as enough space is available.

We have an option to storing the table as row store or column store when we create the table.

We have row store data engine. It is optimized for high performance for write operation.

We use it when we want to write into hana database.

Data is read using column store engine

Tables in row based store are loaded at startup time where as in case of column based store it is loaded at startup on demand (during normal operation on hana db)

Both engines share common persistence layer.

Advantage of Column Store

1. We have faster data access because only the affected column have to be read during selection process of query.
2. Any column can server as an index which provides faster access.
3. We have better compression – because columnar data storage provides highly efficient compression – because majority of column contains few distinct values.
4. We have better parallel processing – data is already vertically partitioned. – So operations on different columns can be easily be processed.
5. If multiple column needs to be searched, then each of the column can be assigned to different processor core for parallel processing.

Advantages of row based:

1. When application needs to process single record in one time.
2. App needs to access whole record (not just column)
3. If table has small no of rows, then it doesn’t make difference if we use row store or column store.

Disadvantage of row bases:

1. In case of analytic applications – where fast search and processing is required – All the data has to be read – even the requirement is to access just few columns

SAP HANA Architecture

Data is compressed by different compression techniques (e.g. dictionary encoding, run length

encoding, sparse encoding, cluster encoding, indirect encoding) in SAP HANA Column store.

When main memory limit is reached in SAP HANA, the whole database objects (table,

view, etc.) that are not used will be unloaded from the main memory and saved into the disk.

These objects names are defined by application semantic and reloaded into main memory from

the disk when required again. Under normal circumstances SAP HANA database manages

unloading and loading of data automatically.

However, the user can load and unload data from individual table manually by selecting a table

in SAP HANA studio in respective Schema- by right-clicking and selecting the option

“Unload/Load”.

SAP HANA Server consists of

1. Index Server
2. Preprocessor Server
3. Name Server
4. Statistics Server
5. XS Engine

1. SAP HANA Index Server

SAP HANA Database Main server is index server.

It contains actual data stores and the engine for processing the data.

Index Server processes incoming SQL or MDX statement.

Data loads, queries, calculation etc. are done here.

Below is the architecture of Index Server.

SAP HANA Index Server overview

1. Session and Transaction Manager: Session Component manage sessions and

connections for SAP HANA database. Transaction Manager coordinates and control

transactions.

2. SQL and MDX Processor: SQL Processor component queries data and send to them in

query processing engine i.e. SQL/SQL Script / R / Calculation Engine. MDX Processor queries

and manipulates Multidimensional data (e.g. Analytic View in SAP HANA).

3. SQL / SQL Script / R / Calculation Engine: This Component executes SQL / SQL script and

calculation data convert in calculation model.

4. Repository: Repository maintain the versioning of SAP HANA metadata object e.g.

(Attribute view, Analytic View, Stored procedure).

5. Persistence layer: This layer uses in-built feature “Disaster Recovery” of SAP HANA

database. Backup is saved in it as save points in the data volume.

2. Preprocessor Server

This server is used in Text Analysis and extracts data from a text when the search function is

used.

3. Name Server

This Server contains all information about the system landscape. In distributed server, the name

server contains information about each running component and location of data on the server.

This server contains information about the server on which data exists.

4. Statistic Server

Statistic server is responsible for collecting the data related to status, resource allocation /

consumption and performance of SAP HANA system.

It is central element of SAP HANA internal monitoring infrastructure.

It notifies when critical alarm arises

It provides historical monitoring data for analysis.

5. XS Server (eXtended Services Engine) – Optional

XS Engine Client connects HANA DB to fetch data via HTTP (say ARIBA)

XS Server contains XS Engine. It allows external application and developers to use SAP HANA

database via the XS Engine client. The external client application can use HTTP to transmit

data via XS engine for HTTP server.

Daemon server

Along with all these we also have Daemon Server

Daemon server is used to start all other servers

It keeps all other processes running.