You cannot risk to perform Untrusted Transactions with Your Business Partners?


ChainifyDB® establishes Trust in Environments, that have been Untrusted so far.

Seamless. Minimally Invasive. Robust. Accessible.




The Problem

Untrusted Transactions in Untrusted Environments.


Today, relationships between companies and organizations generate vast amounts of mutual data. For example, trading companies continuously generate data about the trades they perform with each other. For various reasons, the parties in these relationships somehow have to keep track of this data. Obviously, outsourcing it to a cloud service is often impossible due to a lack of trust against the provider, in particular when dealing with highly sensitive or confidential corporate data.

As a consequence, the mutual data is typically stored individually by all involved parties in their own local databases. By this, all the data remains private between the parties. However, when keeping track of mutual data individually, there is a high risk that the stored data actually differs to some degree across the parties. Reasons for this are manifold, ranging from misinterpretation of data over type conversions to human errors. As a consequence, the databases diverge from each other over time, as shown in the following Figure:



This can lead to far-reaching problems: For example, to this day, doctors and hospitals typically keep track of patient records individually. If these records contradict each other or are incomplete, a faulty or even dangerous treatment can be the consequence. For obvious reasons, a verification of the stored data by a third-party instance is neither practical nor confidential.

This problem is present in various areas, businesses, and markets. For example:

If trading partners have different views on transaction details, disputes can arise retrospectively. These disputes are only resolvable in costly court proceedings.

If in a production or supply chain, it can not be transparently traced when and under which conditions a product was manufactured or redistribution, no well-founded statement about the quality of the goods can be made.

If independent financial institutes, such as banks, want to perform financial transactions with each other, they have to consult a clearinghouse as a middleman. Obviously, this process is costly, slow, and assumes trust with respect to the clearinghouse.

If tickets are supposed to be valid for door-to-door travels, multiple transportation companies are involved at different levels. If there are differences in their ticket databases, passengers might take advantage of it or be compromised.

If a real-world entity, like a car, should be tracked digitally throughout its life, many independent organizations, such as repair shops, insurance companies, and registration offices, get in touch with it. Incomplete or faulty data can have negative consequences for buyers and sellers of these entities.

If patient records stores at medical institutes are contradictory, incomplete, or erroneous, a wrong treatment is the consequence.



If your company maintains data, that is in relation with other organizations, then your are likely facing the same untrusted situation.

Find out more about our solution to this problem.

Our Solution - ChainifyDB®

Equip Your Environment with Trust: Seamless, Minimally Invasive, Robust, Accessible.


ChainifyDB® solves the aforementioned problems. We establish trust in data management environments, that have been untrusted so far.

We do so by utilizing sophisticated blockchain technology. But don't worry: There is no need to rethink your entire infrastructure to leverage this new technology. ChainifyDB® keeps it simple and just integrates the powerful features, that made blockchains famous, into your current corporate landscape.

Effectively, you and your business partners can continue using your local independent database systems as before. At the same time, the ChainifyDB® network established between you and your business partners guarantees that all your mutual data is perfectly synchronized at all times.

The following Figure visualizes an infrastructure equipped with ChainifyDB®:



In contrast to other blockchain solutions on the market, ChainifyDB® is designed from the get-go as a fully seamless experience for our customers. It allows you to:

  • Install ChainifyDB® minimally invasive on top of your established relational database systems.
  • Query your mutual data using classical SQL.
  • Formulate personal constraints on your mutual data, which your partners have to respect.
  • Keep your legacy data and applications untouched and fully functioning.
  • Recover your mutual data in case of external corruption or damage.
  • Utilize high-performance parallel transaction execution across systems.

ChainifyDB®. More details about the features of ChainifyDB® are provided below.

ChainifyDB® Features

Tailored to Your Business Requirements.


Secure your Business Relationships

You can not risk to perform untrusted transactions with your business partners? You want to securely share mutual data with other organizations? You don't want to loose control about your data by moving it into the cloud?

ChainifyDB® establishes trust in environments, that have been untrusted so far. Equip your local infrastructure with sophisticated blockchain features.

  • Execute trusted transactions with your trading partners, which are guaranteed to be executed on all parties in exactly the same way.
  • No trusted third-party instance required to validate transactions.
  • Formulate integrity constraints that must be respected by all parties.


Seamless Integration

You don't want to rethink your entire database infrastructure just to exploit blockchain technology?

Simply install ChainifyDB® on top of your established relational database management system and equip it with sophisticated blockchain features.

  • Your legacy applications will function as before.
  • No data migration to a new system required.
  • New applications can perform trusted transactions.
  • Installation on top of running databases causes zero downtime.


Chainify Your Favorite Relational System

You and your business partners are currently using different database management systems, such as PostgreSQL and MySQL, and you don't want to switch?

No problem. ChainifyDB® is designed to be compatible with a variety of relational database management systems and even enables trusted transactions between different systems.

  • Support for major open-source and commercial relational systems.
  • Your favorite system is currently not officially supported? Contact us to discuss the compatibility of your system.


Keep it Simple: Access Your Data using SQL

You don't want to rewrite your applications to work with complicated blockchain languages and interfaces?

Hyperledger Fabric Smart Contract in Golang
 0  func(t *Chaincode) Deposit(stub shim.ChaincodeStubInterface,
                                        args []string) pb.Response {
 1    if len(args) != 2 {
 2      return errormsg(ERROR_WRONG_ARGS + " send_payment")
 3    }
 4    key := accountKey(args[1])
 5    accountBytes, err := stub.GetState(key)
 6    if err != nil { return errormsg(ERR_NOT_FOUND) }
 7    destAccount := Account{}
 8    err = json.Unmarshal(accountBytes, &res)
 9    if err != nil { return errormsg(ERR_NOT_FOUND) }
10     amount, _ := strconv.Atoi(args[0])
11     destAccount.checkingBalance += amount
12     accountBytes, err := json.Marshal(destAccount)
13     if err != nil { return errormsg(ERROR_PUT_STATE) }
14     key := accountKey(destAccount.CustomId)
15     err = stub.PutState(key, accountBytes)
16     if err != nil { return errormsg(ERROR_PUT_STATE) }
17     return shim.Success(nil)
18  }

Query your chainified relational database management system as before - using simple SQL.

SQL
0  BEGIN TRANSACTION
1 UPDATE Accounts
2    SET checkingBalance = checkingBalance + amount
3  WHERE acc = destAccount
4 COMMIT


Robustness for your Business

Your don't want to worry about your data or the one of your trading partners getting damaged?

In case of data corruption or loss due to external causes, ChainifyDB® restores your data and the one of your partners always to a consistent state. Consequently, your data and thus your business is never at risk.

Team

Academic skills transitioned to industry.


Dr. Felix Schuhknecht

Felix Martin Schuhknecht

Felix Martin Schuhknecht is a postdoctoral researcher in the Big Data Analytics Group of Prof. Jens Dittrich in the Computer Science Department of Saarland University, where he finished his Ph.D. studies in 2016. His research focuses on blockchain technology, transactional processing, main-memory (adaptive) indexing methods, data partitioning and sorting, storage layouts, and memory management techniques. He has published work in these areas on major conferences, journals, and workshops in the field of databases and information systems, including PVLDB/VLDB, VLDB Journal, SIGMOD, ICDE, CIDR, SIGMOD DaMoN, and BTW. In 2014, he won a VLDB best paper award (the second ever given to an Experiments and Analysis paper) on a study about adaptive indexing. Besides, he is a member of several program committees such as SIGMOD 2020, ICDE 2020, BTW 2019, VLDB 2018 demo track, and CIKM 2018.


Ankur Sharma

Felix Martin Schuhknecht

Ankur Sharma is a PhD student of Computer Science at Saarland University since 2016. He is working in areas revolving around memory management and performance optimizations in transactional information systems. His recent works include efficient user-space snapshotting as well as integrating high-frequency snapshotting inside the linux kernel which can heavily improve the throughput of HTAP engines. He is also working on improving query optimizers of production-ready Systems like Postgres using Deep Learning. He has published in the top-tier big data conference VLDB and has served as an external reviewer in several prestigious conferences such as ACM SIGMOD, VLDB and ICDE. He enjoys hacking critical performance bottlenecks using better algorithms, memory-management, and machine learning.


Prof. Dr. Jens Dittrich

Felix Martin Schuhknecht

Jens Dittrich is a Full Professor of Computer Science in the area of Databases, Data Management, and Big Data at Saarland University, Germany. Previous affiliations include U Marburg, SAP AG, and ETH Zurich. He received an Outrageous Ideas and Vision Paper Award at CIDR 2011 (conference on Innovative Data Systems Research), a BMBF VIP Grant in 2011, a best paper award at VLDB 2014 (Conference on Very Large Data Bases), two CS teaching awards in 2011 and 2013, as well as several presentation awards including a qualification for the interdisciplinary German science slam finals in 2012 and three presentation awards at CIDR (2011, 2013, and 2015). He has been a PC member and area chair/group leader of prestigious international database conferences and journals such as PVLDB/VLDB, SIGMOD, ICDE, and VLDB Journal. He is on the scientific advisory board of Software AG.


Open Positions

Join the team and become a part of ChainifyDB.


Software Engineer (m/w/x)

We are current looking for multiple software engineers / research assistants. Details are available here.


Business Developer (m/w/x)

We are current looking for multiple business developers / research assistants. Details are available here.


Contact Us

Call

+49 681 302 70146

Visit

Campus E1.1, 3.09
Saarland Informatics Campus
66123 Saarbr├╝cken
Germany