Get SAP data to Snowflake
Why you should use BryteFlow to get your SAP data to Snowflake
If you have to migrate SAP data or load SAP data to Snowflake, you may be in a quandary as to which SAP replication tool to use. There are a lot of automated data replication tools out there that will ETL your SAP data to the Snowflake data warehouse. But exactly how efficient are they? SAP Application level replication is very slow and time consuming. There are some points you may need to consider before committing to a data replication tool. SAP to AWS (Specifically S3) – Know as Easy Method
BryteFlow supports flexible connections to SAP including: Database logs, ECC, HANA, S/4HANA and SAP Data Services. It also supports Pool and Cluster tables. The SAP Cloud Connector and Why It’s So Amazing
Learn about BryteFlow for SAP
SAP ETL Tool: Extract data from SAP systems with business logic intact
- Low latency, log based replication with minimal impact on source. Replication with SAP SLT
- BryteFlow data replication uses very low compute so you can reduce Snowflake data costs. Why You Need Snowflake Stages
- No coding needed, automated interface creates exact replica or SCD type2 history on Snowflake. SAP HANA to Snowflake (2 Easy Ways)
- Manage large volumes easily with automated partitioning mechanisms for high speed. About SAP BODS
How to load terabytes of data to Snowflake fast
CDS View on SAP HANA and how to create one
SAP Extraction using ODP and SAP OData Services (2 Easy Methods)
Real-time, codeless, automated SAP data replication to Snowflake
Can your replication tool replicate really, really large volumes of SAP data to your Snowflake database 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 SAP data to Snowflake at super-fast speeds. You can also limit the number of records by providing date or any other data restrictions very easily.
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 Snowflake and transformation are completely automated?
This is a big one. Most SAP ETL tools will set up connectors and pipelines to get your SAP data to Snowflake but there is usually coding involved at some point for e.g. to merge data to the original data set. 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 Snowflake 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 Snowflake at 2pm on Thursday, Nov. 2019, all the changes that happened till that point will be replicated to the Snowflake 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 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 zero impact Change data capture technology and uses database transaction logs to query data at source and copies only the changes into the Snowflake database. The data in the Snowflake data warehouse is updated in real-time or at a frequency of your choice. Log based CDC is absolutely the fastest, most efficient way to replicate your SAP data to Snowflake.
Does your data maintain Referential Integrity?
With BryteFlow you can maintain the referential integrity of your data when replicating SAP data to Snowflake. 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 (Snowflake) 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 Snowflake cloud data warehouse?
With BryteFlow, data in the Snowflake cloud data warehouse is validated against data in the SAP source 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 source database and Snowflake 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.
Support for flexible connections to SAP
BryteFlow supports flexible connections to SAP including: Database logs, ECC, HANA, S/4HANA and SAP Data Services. It also supports Pool and Cluster tables. Import any kind of data from SAP into Snowflake with BryteFlow. It will automatically create the tables on Snowflake so you don’t need to bother with any manual coding.
BryteFlow creates a data lake on Snowflake so the data model is as is in source – no modification needed
BryteFlow converts various SAP domain values to standard and consistent data types on the destination. For instance, dates are stored as separate domain values in SAP and sometimes dates and times are separated. BryteFlow provides a GUI to convert these automatically to a date data type on the destination, or to combine date and time into timestamp fields on the destination. This is maintained through the initial sync and the incremental sync by BryteFlow.
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 Snowflake process over again? Yes, with most software but not with BryteFlow. You can simply pick up where you left off – automatically.
SAP HANA to Snowflake (2 Easy Ways)
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 SAP data for Analytics or Machine Learning.
About SAP
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 Snowflake Data Warehouse
The Snowflake Data Warehouse or Snowflake as it is popularly known is a cloud based data warehouse that is extremely scalable and high performance. It is a SaaS (Software as a Service) solution based on ANSI SQL with a unique architecture. Snowflake’s architecture uses a hybrid of traditional shared-disk and shared-nothing architectures. Users can get to creating tables and start querying them with a minimum of preliminary administration.