Replicate SAP data to Redshift
Get SAP data to Redshift in real-time, easily and without any coding
Need to replicate SAP data to Redshift? Wondering which SAP replication tool to use? You can find quite a few automated data replication tools that will ETL your SAP data to Redshift, but most will lack the important features needed to make your SAP data replication as fast and smooth as possible – we will elaborate on these shortly. Our software BryteFlow supports flexible connections to SAP including: Database logs, ECC, HANA, S/4HANA and SAP Data Services. It also supports Pool and Cluster tables.
Learn about BryteFlow for SAP
Why migrate SAP data to Redshift with BryteFlow
- Low latency, log based replication with minimal impact on source.
- Optimised for Redshift, dist keys and sort keys are created automatically.
- No coding needed, automated interface creates exact replica or SCD type2 history on Redshift.
- Manage large volumes easily with automated partitioning mechanisms for high speed.
- S3 and Redshift can be loaded in parallel – saves time.
Real-time, codeless, automated SAP data replication to Redshift
Can your replication tool replicate really, really large volumes of SAP data to your Redshift data warehouse fast?
When your data tables are true Godzillas, including SAP data, most data replication software roll over and die. Not BryteFlow. It tackles terabytes of data for SAP replication head-on. BryteFlow XL Ingest has been specially created to replicate huge SQL data to Redshift at super-fast speeds.
Try BryteFlow free and see the difference.
Access Operational Metadata out of the box
BryteFlow keeps operational metadata out of the box of all the extraction and load processes. This can be saved on Aurora if required. The metadata includes currency of data and data lineage. Currency of data shows the status of the data whether it is active, archived, or purged. Data lineage represents the history of the migrated data and transformation applied on it.
Prepare data on Amazon S3 and copy to Amazon Redshift or use Redshift Spectrum to query data on Redshift
BryteFlow provides the option of preparing data on Redshift and to copy it to Redshift for complex querying. Or you can use Redshift Spectrum to query the data on Redshift without actually loading it onto Amazon Redshift. This distributes the data processing load over S3 and Redshift saving hugely on processing and storage cost and time.
How much time do your Database Administrators need to spend on managing the replication?
You need to work out how much time your DBAs will need to spend on the solution, in managing backups, managing dependencies until the changes have been processed, in configuring full backups and then work out the true Total Cost of Ownership (TCO) of the solution. The replication user in most of these replication scenarios needs to have the highest sysadmin privileges.
With BryteFlow, it is “set and forget”. There is no involvement from the DBAs required on a continual basis, hence the TCO is much lower. Further, you do not need sysadmin privileges for the replication user.
Are you sure SAP replication to Redshift and transformation are completely automated?
This is a big one. Most SAP data tools will set up connectors and pipelines to stream your SAP data to Redshift but there is usually coding involved at some point for e.g. to merge data for basic SAP CDC. With BryteFlow you never face any of those annoyances. SAP data replication, data merges, SCD Type2 history, data transformation and data reconciliation are all automated and self-service with a point and click interface that ordinary business users can use with ease.
Is your data from SAP to Redshift monitored for data completeness from start to finish?
BryteFlow provides end-to-end monitoring of data. Reliability is our strong focus as the success of the analytics projects depends on this reliability. Unlike other software which set up connectors and pipelines to SAP source applications and stream your data without checking the data accuracy or completeness, BryteFlow makes it a point to track your data. For e.g. if you are replicating SAP data to Redshift at 2pm on Thursday, Nov. 2019, all the changes that happened till that point will be replicated to the Redshift database, latest change last so the data will be replicated with all inserts, deletes and changes present at source at that point in time.
Does your data integration software use time-consuming ETL or efficient SAP CDC to replicate changes?
Very often software depends on a full refresh to update destination data with changes at source. This is time -consuming and affects source systems negatively, impacting
productivity and performance. BryteFlow uses SAP CDC to Redshift which is zero impact and uses database transaction logs to query SAP data at source and copies only the changes into the Redshift database. The data in Redshift is updated in real-time or at a frequency of your choice. Log based SAP CDC is absolutely the fastest, most efficient way to replicate your SAP data to the Redshift data warehouse.
Does your data maintain Referential Integrity?
With BryteFlow you can maintain the referential integrity of your data when replicating SAP data to AWS Redshift. What does this mean? Simply put, it means when there are changes in the SAP source and when those changes are replicated to the destination (Redshift) you can put your finger exactly on the date, the time and the values that changed at the columnar level.
Is your data continually reconciled in the Redshift data lake?
With BryteFlow, data in the Redshift data warehouse is validated against data in the SAP replication database continually or you can choose a frequency for this to happen. It performs point-in-time data completeness checks for complete datasets including type-2. It compares row counts and columns checksum in the SAP replication database and Redshift data at a very granular level. Very few data integration software provide this feature.
Do you have the option to archive data while preserving SCD Type 2 history?
BryteFlow does. It provides time-stamped data and the versioning feature allows you to retrieve data from any point on the timeline. This versioning feature is a ‘must have’ for historical and predictive trend analysis.
Can your data get automatic catch-up from network dropout?
If there is a power outage or network failure will you need to start the SAP data replication to Redshift process over again? Yes, with most software but not with BryteFlow. You can simply pick up where you left off – automatically.
Can your SAP data be merged with data from other sources?
With BryteFlow you can merge any kind of data from multiple sources with your data from SAP for Analytics or Machine Learning.
More on BryteFlow’s Data Integration for Redshift
BryteFlow’s Data Integration Tools
The BryteFlow software consists of data integration tools that work synergistically to deliver flawlessly
replicated, prepared data that you can use for your Analytics, ML, AI or other applications.
Get a FREE Trial now
BryteFlow ControlRoom: our data monitoring tool
The Bryteflow ControlRoom is an operational dashboard that monitors all instances of BryteFlow Ingest and BryteFlow Blend, displaying the statuses of various replication and transform instances.
About BryteFlow ControlRoom
SAP is an acronym for Systems Applications and Products in Data Processing. SAP is an Enterprise Resource Planning) software. It consists of a number of fully integrated modules, which cover most business functions like production, inventory, sales, finance, HR and more. SAP provides information across the organization in real-time adding to productivity and effiency. SAP legacy databases are typically quite huge and sometimes SAP data can be challenging to extract.
About Amazon Redshift
Amazon Redshift is the fully managed , petabyte scale cloud data warehouse of AWS. Amazon Redshift is characterized by its super fast speed in executing queries against large datasets aided by its Massively Parallel Processing and columnar database. Redshift is comprised of nodes (computing resources) that are organized in clusters. Each Redshift cluster has its own processing engine and at least one database. On Redshift, processing power can be scaled up immediately by adding more nodes to your cluster or even spinning up more clusters.