Data replication
and data migration
software

Repstance is real-time replication tool for SQL Server and Oracle databases, which has highly advanced replication and transformation abilities.
Repstance is currently listed on the AWS and Azure platforms and supports:
Oracle 10G - 19C and any version of SQL Server that permits the use of CDC (Change Data Capture) as Source Databases. Oracle 10G - 19C, SQL Server, MySQL, PostgreSQL, Amazon Aurora, Amazon Redshift, Snowflake and S3 as Target Systems.

Deliver your data to multiple consumers with only one tool

Very high speed of data migration and replication
Minimal impact on Source Databases
Native support of DDL operations
Advanced data transformations and filtering abilities
Support of multiple complex replication topologies
Easy to deploy, monitor and maintain
API to integrate with 3rd party software
Extensive forensic reporting functions
Use Cases where Repstance Excelles
Technical scope:
Simultaneious migration of 20 databases from SQL Server to Aurora PostgreSQL
Total size of the databases:
20 TB
Number of tables:
8,000
Daily data change volume:
around 150Gb
Transformation required (y/n):
yes
Data comparison/validation:
yes, 100% deep
Downtime allowed:
under 30 mins
Do you also have a difficult case?
We did the impossible when others couldn't
Fintech

Goal:
OnPrem SQL Server to AWS Aurora PostgreSQL migration

Business Justification:
This migration was needed to optimize costs related to current setup (onPrem) and reduction in unnecessary licensing and integration with cloud infrastructure with additional technological benefits

Challenges:

Databases structure in Aurora and SQL Server are not similar – such migration requires complex customised data transformations. Since fintech is extremely sensitive about data integrity – in this scenario deep data validation and comparison between source and target is an absolute must with 100% match. Extremely stringent requirements for downtime and data quality meant that other solutions failed to deliver the desired results.

Repstance approach:

  • Two distributed EC2 instances (m5.4xlarge) were used
  • Over 70 transformation rules affecting 6,000 objects were developed
  • Initial data migration and ongoing replication was set up
  • Full data comparison to validate 20 TB of data was executed in parallel with ongoing data replication
  • Incremental data comparison was running daily only to validate the data that was changed since the last validation point (average daily change size – 150 GB)
  • The last incremental data comparison was executed as part of the cutover procedure to ensure full data integrity between both source and target databases
Technical scope:
Onprem SQL Server 2016 to SQL server – ongoing replication
Total size of the databases:
7 TB
Number of tables:
60,000
Daily data change volume:
20GB
Transformation required (y/n):
no
Data comparison/validation:
yes
Replication Lag:
under 15 mins
Do you also have a difficult case?
We did the impossible when others couldn't
Healthcare

Goal:  

Onprem SQL Server 2016 to SQL Server – ongoing replication

Business justification:

Need to unload the production system by moving BI/reporting functionality to the mirrored instance without any interruptions 

Challenges:

Too many tables (60,000) with ongoing DDL and DML operations along with uneven load and "15 mins lag" requirement is making it expremely hard to handle with any other solutions

Repstance approach:

  • Onprem version of Repstance instance was used. Initial data migration was initiated with native MSSQL backup/recovery.
  • Repstance was configured to replicate data from the point when backup was taken.
  • After that data was validated both on source and target with 10% depth (for quick validation).
  • System monitoring was configured to flag any incidents related to replication errors or lag exceeding 15 mins.

 

Technical scope:
Simultaneous ongoing replication of up to 10 databases
Total size of the databases:
200 GB to 15 TB
Number of tables:
3,000
Daily data change volume:
1 GB to 150 GB
Transformation required (y/n):
yes
Data comparison/validation:
no
Replication Lag:
under 3 mins (business critical)
Do you also have a difficult case?
We did the impossible when others couldn't
Software Development and IT

Goal:

Implement zero downtime upgrade for SQL Server databases 

Business justification:

Client needs to roll out timely and reliable updates/patches/etc for their end users to keep users constantly up to date with the latest changes in the product

Challenges:

The biggest challenge is related to a very small change window (under 3 mins) because product is used in mission critical scenarios by end users.  The second challenge is related to complex transformation and data manipulation because of the differences in database versions across source and target databases. 

Repstance approach:

  • Customer uses Repstance as a part of the deployment process to replicate data between databases running different versions of the product and implementing bespoke data processing logic
  • The deployment of Repstance instance is fully automated with Terraform and Repstance REST API
  • All databases are fully synchronised and the end users seamlessly switch to the new version in under 3 mins
Technical scope:
Oracle to S3 and SnowFlake replication
Total size of the databases:
13 TB
Number of tables:
1,500
Table partitions count:
600,000
Daily data change volume:
over 200 GB
Transformation required (y/n):
yes
Data comparison/validation:
no
Replication lag:
under 30 mins
Do you also have a difficult case?
We did the impossible when others couldn't
Telecom

Goal:

Initial data load and ongoing data replication from Oracle to S3 and SnowFlake 

Business justification:

Data needs to be delivered to end user’s partners either to S3 or SnowFlake to address specific business needs (daily data flow).  This data is used for decision making, reporting, and deep data analysis. 

Challenges:

Because of the large number of partitions and constant partitions being added other products were not able to meet data delivery speed requirements.  Long running transactions are typical for this customer’s database and this made the task even more complex.

Repstance approach:

  • Repstance used one capture to extract data from Oracle and two applies to propagate collected data to S3 and SnowFlake
  • Replication was configured to capture data changes from the standby REDO logs to avoid impact on the Source database
  • Based on the defined filtering and transformation rules the data was accurately distributed to required destination
  • Speed of DDL changes processing allowed to overcome the challenge of added partitions
  • Unlike other solutions, Repstance does not have performance issues when processing long transactions, which was the main criterion for choosing a replication product
Technical scope:
Reporting data replication from Oracle to Aurora PostgreSQL
Total size of the databases:
8 TB
Number of tables:
1,000
Daily data change volume:
over 150 GB
Transformation required (y/n):
yes
Data comparison/validation:
no
Replication Lag:
under 30 mins
Do you also have a difficult case?
We did the impossible when others couldn't
Fintech

Goal:
Setup replication from Oracle 19c RAC (4 nodes) standby database to AWS Aurora PostgreSQL

Business justification:

The data needs to be replicated to an Aurora PostgreSQL database for business analytics and reporting

Challenges:

Source databased needs to have minimal possible impact during the replication

Repstance approach:

  • Repstance was using direct log mining mode to extract data changes from Oracle REDO logs that were taken from standby instance (ASM device)
  • Repstance did not need to interact with the primary source database and completely minimised the replication impact
  • In accordance with the customer's security policy, the Source and Target databases must be isolated. Under these curcumstances 2 Repstance instances were used, one to extact data from the Source database and another to apply the changes to the Target database. The interaction between Repstance instances were established via S3
Repstance Benchmark Performance
for Medium-Loadaded Oracle Database
Repstance
Repstance Advanced Edition version 5.2.0189
m5.2xlarge
Source Database
AWS RDS Oracle Enterprise Edition 19c
db.m5.4xlarge
Target Database
AWS RDS Aurora Compatible with PostgreSQL 16.6
db.r5.2xlarge
Stress-Test Tool
SwingBench. Oracle OrderEntry benchmark
-
Initial Data Load
Data Loading Speed:
72 GB/hour
Number of Loaded Records:
584 Millions/hour
Ongoing Data Replication
Redo Logs Processing Speed:
42 GB/hour
Number of Replicated Data Changes:
72 Millions/hour
Data Comparison
Data Validation Speed:
42 GB/hour
Number of Validated Records:
328 Millions/hour
Replication LAG
Max:
22 sec
Average:
2.5 sec
Replication Impact on the Source Database
Max:
3.2%
Average:
1.2%
Replication Impact on the Target Database
Max:
2.8%
Avarage:
1.1%
Why Repstance?

Repstance is an extremely reliable
Database migration and replication tool!

Repstance has been created as a product that propagates the maximum amount of data at the highest possible speed with minimal impact on the source and target databases and the highest possible degree of security and integrity.

It was designed to be a very easy to use and secure solution that will meet the most demanding and complex environment requirements for optimal data replication and migration tasks.
Migration & Replication

As a premier data transfer tool, Repstance is used by companies to solve multiple types of tasks - from simple migrations to complex and ongoing replications.

Request a Demo

 

Initial Data Load

Repstance Initial Load functionality is used to copy a high volume of data from the source to the target database.

To achieve the best performance, Initial Load uses various database features such as:

  • "bulk load"
  • "parallelism"
  • "staging load"

which allows Repstance to quickly move the initial set of objects and data without having any additional tools involved in the synchronization process.

Initial load is extremely useful when it is necessary to transfer tables taking into consideration: data type remapping, data conversion, object naming, any transformation rules, and especially in heterogeneous replication scenarios, such as:

  • Oracle to Snowflake data replication
  • data migration from SQL Server to PostgreSQL
  • etc.
Ongoing Data Replication

Repstance has the functionality to support Data Modification Language (DML) and Data Definition Language (DDL) operations, which can be automatically included in the replication stream and, if desired, uses sophisticated transformation and data filtering abilities.

Repstance implements sophisticated deeply researched algorithms that extract and apply data, depending on:

  • number of objects being changed;
  • number of changes;
  • types of changes;
  • specifics of transactions;

Which is how it makes Repstance replications one of the fastest amongst any other solution.

Enabling DDL replication forces Repstance to track and replicate any structural changes occurring to tables including, but not limited, to table creating, dropping, and renaming tables, any columns’ modifications, adding and dropping partitions, sub-partitions, modification of primary keys and unique indexes. These changes are automatically included during DML replication and do not require any manual User intervention.

Repstance propagates data into the Target Database in the same order they were executed in the Source Database, which means that both Source and Target Databases will be synchronized in a “Consistent State”.

The data extracted by the Capture Process is written to the Trail Files in the same sequential order as the transactions that occurred in the Source Database, which in turn allows the Apply Process to insert this data into the Target Database in the same order they were executed in the Source Database. This means that both Source and Target Databases will be synchronized and keep your data entirely consistent across all your databases.

Transformation and Data Filtering

Repstance supports various types of data transformation and filtering, which are primarily used where there is a need to reformat any statements. Using transformations allows replicating data between tables with different structures, adding custom data processing logic, using SQL functions for data processing and enrichment, etc.

Transformations can also be enabled for DDL replication, meaning that any DDL statements will also be affected by the transformation rules.

Transformations are widely used for various Zero Downtime Upgrade or Blue Green Upgrade scenarios when it is necessary to support replication for databases that are running on different versions.

Filtering capability allows specifying of a subset of data using SQL-based conditions, which are not affected by DML operations. For example, using filters, you can prohibit the cleaning of any data, giving you the means to restore it from the target database, if data was deleted by mistake, or not to permit the insertion of sensitive data into the target system, etc.

Supported Databases

Instead of covering all the possible source and target database types, as an excellent Data replication tool supplier we focused on the most popular ones. These are Oracle and SQL Server - as such we really excel in them!

Repstance fully supports heterogeneous data propagation, meaning that data from Oracle or SQL Server databases can be replicated into any of supported Target databases, which are:

  • Oracle
  • SQL Server
  • PostgreSQL
  • Aurora (using either PostgreSQL or MySQL engines)
  • MySQL
  • MariaDB
  • Redshift
  • Snowflake
  • AWS S3

Repstance has a wide range of parameters allowing you to customize and fine-tune the replication process to meet complex data propagation requirements and successfully function when others failed.

Interface with Repstance

As a premier Data replication tool supplier we provide different configuration approaches.

Our product is available as an out-of-the-box cloud solution in both AWS and Azure marketplaces. It gives you the ability to set up everything as fast as possible.

To meet specific needs we provide custom on-premises deployment versions. Since we do our best to make complex migration and replication tasks as simple as possible, we create a few ways to interact with Repstance:

WebUI. Web application to easily configure replication/data migration via a Web browser.
Repcli. This is the command line version of WebUI.
JSON. Repstance supports JSON API allowing us to configure the processes programmatically.

WebUI is an easy and intuitive way to configure replication using a Web browser only, while Repcli and JSON are primarily used to integrate Repstance with external tools and deployment systems such as Terraform or Cloud Formation.

Support

We understand the value of your data and pay special attention to our client's support.

Our support team is available 24/7 and provides extensive expertise as standard including, but not limited to choosing the best configuration based on your needs.

Our experts can walk through all the steps of the process of maintaining Repstance from start to finish.

Contact our support team and we will schedule a call to demonstrate Repstance’s capabilities and discuss all your needs.

If Repstance meets your requirements we will provide you trial licenses and full support of the product. Our technical specialists have deep knowledge and expertise in data migration and replication projects and are happy to review your databases to advise on the best approach, help with product setup and configuration, and participate in POC implementation.

With our support team, you will be able to evaluate Repstance in your environments without the necessity to buy it.

contact support