How does the high-level architecture of Teradata compare to Amazon Redshift?
For Teradata Nodes, AMPs, BYTNET, and Parsing Engine there is a Corresponding counterpart in Amazon Redshift: The Slices. Slices in Amazon Redshift can be viewed as standalone computers, each Slit has its own CPU, memory, and information. Similar to Teradata, pieces are linked over a network.
What's the data of a desk spread in Amazon Redshift? The initial distribution of the data is analogous to Teradata. Here all Massive parallel systems are similar: hashing is used. Back in Teradata, the primary indicator is employed for this function. An equivalent Into the key Index in Teradata is your Distkey at Amazon Redshift.
As the Primary Indicator describes the AMP holding a row, the Distkey is utilized to recognize the correct slit if the WHERE state of the SQL statement comprises the column that's defined as Distkey. What makes Teradata Columnar different from Redshift Columnar? Amazon Redshift distributes the data across all slices and then divides Them into columns.
The columns of a row are assigned to cubes so that they can easily be found together again.
Each block contains metadata that stores the value range of the block. This helps to not read blocks if they don't include the values you are looking for. Teradata provides storage of columnar tables in different ways, but it reconstructs rows.
In a subsequent step, the row-based classic database engine does its own work. Is there an equivalent to Teradata Partitioned Primary Index Tables? That's what the sortkey in Amazon Redshift is for. Are there any secondary indexes in Amazon Redshift enjoy in Teradata? No, but let us be honest: How often do you use a NUSI or USI in Teradata?
And if so, isn't it always difficult to design it to be used? In Teradata, statistics must be appropriate, selectivity has to be right, etc.. Amazon Redshift uses an innovative Way of performance tuning:
For every data block, the value range is stored in metadata. This allows Amazon Redshift to limit the search to information to blocks that match the WHERE condition. What do Amazon Redshift data cubes look like? As in Teradata, the dimensions of the data blocks is lively.
In Amazon Redshift, a data block develops up to a size of one megabyte, then the data block is split into two blocks of equal size. How can unites work in Amazon Redshift? In this respect Redshift is not very distinct from Teradata: The information Must be about exactly the exact same piece to be joined. If the distkey of both tables is the same, then the data of both tables Are already on exactly the same slice.
But how can you prevent information from being copied throughout the link? Amazon Redshift lets you copy a table to all slices in advance. Even though Teradata can choose this strategy throughout the join to bring the Rows on a frequent AMP, this is sometimes found in Redshift.