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Guide to real-time data sharing vendor types

Want to scale up and streamline your real-time data sharing capabilities? Explore five common vendor approaches and compare and contrast them with Vendia.

Alexa Johnson
Head of Content Strategy

Last updated: October 18, 2022

Guide to real-time data sharing vendor types

Real-time data sharing facilitates informed decision-making by making data available as soon as it’s created or acquired amongst multiple business network partners. With real-time data sharing inside and outside your four walls, you can get insights into improving your customer experience, developing better products and services, and creating efficiencies in your business processes.

But, moving, storing, and managing data (especially large batches of data across clouds, regions, and companies) in a way that’s visible, transparent, and compliant has, historically, been fraught with obstacles, including infrastructure and resourcing challenges.

That’s where a next-gen real-time data sharing solution comes into the picture.

Benefits of a real-time data sharing vendor

A real-time data sharing solution feeds your organization with up-to-date data and simplifies the mechanics of data sharing across and between organizations. Here are the main benefits of using a reliable real-time data sharing vendor, including a secure data exchange, an indisputable and single source of truth, and greater scalability.

Secure data exchange

Real-time data sharing vendors are purpose-built to let companies fully control what they share — or don’t share — to ensure the exchange of relevant and required data with partners.

In other words, you don’t have to give third-parties full access to your full data, and you can minimize the risk of sharing intellectual property or other sensitive assets. Most vendors, like Vendia, are also SOC 2-certified, further enhancing the safety of your data.

Indisputable, single-source of truth

A real-time data-sharing solution maintains data integrity, where the accuracy and consistency before and after the transfer remains the same.

  • There is automatic data reconciliation at all times.
  • Every transaction (as well as any changes made) is recorded on every party's ledger, simultaneously, to ensure complete transparency and visibility into current and past states.
  • You can also audit prior transactions to settle disputes and uncover other insights.

Greater scalability without inflating costs

With a next-gen real-time data sharing vendor, you can outsource and simplify what would have been a time-consuming, costly, and complex DIY solution and trade up for a lean app solution. You also free up your team’s bandwidth for less drudgery and more rewarding, impactful work.

After all, your IT environment likely produces or is responsible for managing large volumes of data. When you process and analyze this data in real time and make it available to others in your data ecosystem, you get access to critical information that affords timely insights you can use to tailor products, customer experiences, and even personalization.

Additionally, processing real-time infrastructure data helps IT admin to detect system faults before they impact customers as well as predict and prevent errors, which is a significant advantage considering the average early downtime costs as much as $400,000.

When you involve a real-time data sharing vendor in the mix, you share point-to-point (P2P) streaming data without having to purchase additional infrastructure. This saves you on a significant upfront costs for sharing data at scale, even between different network and system infrastructures.

5 real-time data sharing vendor types

Considering the impact and importance of real-time data sharing in a modern IT environment, you need to carefully evaluate and pick a real-time data sharing vendor capable of delivering on your organization’s broad set of needs.

The good news is there are several vendor approaches to consider. The bad news is not all of them will effectively satisfy your requirements.

Type 1: EAI/iPaaS to move/share/integrate data

Enterprise application integration (EAI), is the traditional approach to sharing data among applications. It’s also known as integration platform-as-a-service (iPaaS). They send data to and from business applications using an intermediary integration platform, decoupling the applications from one another and therefore agnostic to their respective applications and data structures.

These approaches allow connected enterprise applications and data sources to auto-share data and business processes quickly across teams and functions, from one application to another (ex. from sales to accounting). While these solutions may use pre-built connectors and business logic to move your data from point to point, they’re not effective for giving a Customer 360° view without creating more complex workflows (and, as such, can be rife with hidden costs).

These solutions (and their associated toolsets) help cut down the cost of building solutions since their main selling point is serving as an intermediary that forces applications to talk to one another or “connect to everything.” But, pulling this off is harder than vendors lead buyers to believe.

Advantages

  • Streamlined data exchange
  • Reduces P2P integrations of business applications
  • Allows for leveraging a single connector across multiple targets (like a data warehouse to an ERP)
  • Helps save time and minimize human error
  • Reduced labor costs

Disadvantages

  • Overly complex “in the middle” after connecting to each application
  • Challenging to incorporate the business logic that must happen when moving data across applications
  • Risk of accidental data exposure

Type 2: ERP systems to store and use data

Enterprise resource planning (ERP) solutions have an “intra-application” integration and data sharing capability that works among their components. They are business applications that have complex data storage structures directly related to functions like resource planning, accounting, and inventory management. If your organization has large, IT-spanning deployments of SAP or similar software, you can use an ERP solution to address most of your in-house data availability challenges.

While this is certainly desirable, ERP systems also pose a significant challenge: They end at the boundary of the ERP solution.

Suppose you’re in a complex supply chain partnership like the semiconductor industry, and your business partner or a recently acquired subsidiary doesn’t use the same ERP solution — or doesn’t have a traditional ERP deployment, at all. In this case, your system won’t be able to share data or integrate application components.

What’s more, a traditional ERP solution is a pre-cloud development, making them artifacts of their time and requiring complex, platform-specific data models. This ends up limiting its flexibility to adopt modern cloud services.

Advantages

  • Streamlined workflows
  • Improved data accessibility and security
  • Improved communication

Disadvantages

  • Slow data migration
  • Mandatory same-choice ERP systems to share data or integrate AAP components
  • Expensive (requires both heavy upfront and ongoing investment)

Type 3: Public cloud platforms to store and build on data

Currently, there are three main public cloud providers: AWS, Google, and Microsoft.

Each of these providers delivers their services over the internet or via dedicated connections, offering a wide range of services, including fully managed solutions for data storage and databases and infrastructure rental (also known as infrastructure-as-a-service or IaaS). They also use a pay-per-use approach.

Public cloud platforms offering a diverse and broad range of services is one of their key advantages — but, at the same time, it’s a critical disadvantage.

Transforming such a powerful suite of individual services into a scalable and secure solution capable of eliminating real-time data sharing challenges requires a lot of heavy lifting. More importantly, if you consider the main characteristics of a public cloud platform, you’ll find they are traditionally designed to be “walled gardens.” So, if a public cloud provider tries to simplify or streamline data sharing with another public cloud, it may lead to severe consequences.

For example, a public cloud's feature sets and data transfer pricing are designed to facilitate sharing data and integrating solutions within their own native services, which makes using competitive services both complicated and expensive. While it’s a solid business strategy from the public cloud vendor to discourage the adoption of rival platforms, it does limit customers to adopt more innovative solutions.

Advantages

  • Enhanced reliability for maximum uptime
  • Disaster recovery
  • Improved scalability and flexibility

Disadvantages

  • Possible security and compliance issues
  • Requires bespoke solutions to access, harness, and share data
  • Tends to be expensive

Type 4: Conventional data lakes to store data

Data lakes are storage repositories that store significant amounts of data in their raw, native format. Data lakes vendors help you pool all your data in a single place, and data lakes give you the flexibility to “load first and think later.”

However, they lack critical capabilities necessary for real-time operational data sharing and application connectivity. These vendors’ operational systems’ connectivity is also limited to ETL-based ingestion connections and, at times, “reverse ETL” solutions to leverage analytics for the tuning and feedback loops of operational systems.

Getting the data to your data lake can add lag time if it’s not done with the right real-time data tools. So, having a tool in your architecture that can consume this semi-structured data and make it available across all nodes of a cross-cloud architecture enables you to more effectively access your data and turn it into something usable.

Advantages

  • High-level architecture for easy scaling
  • Superior storage capacity
  • Access to big data analytics tools

Disadvantages

  • Data quality issues can stem from complex reconciliation when combining/pooling data from disparate sources
  • Security risks

Type 5: Legacy blockchains to store and govern data availability

When it comes to real-time data sharing, legacy blockchains have a completely different approach compared to P2P EAI and classic cloud-based platforms. Legacy blockchain uses decentralized technology to create an integrated source of truth while maintaining separate stores of data for each party involved.

Under this arrangement, each party possesses a self-governed, operationally isolated copy of the data. Thanks to the unique setup of blockchain-based vendors, this data is always consistent and up to date for all parties, along with cryptographic guarantees. In turn, this simplifies the challenge of building P2P solutions and keeps data consistent always.

The issue here is that legacy blockchains are not the right operational fit for enterprise use cases. Issues like high latency and costs, low throughput, limited scalability, and fault tolerance, combined with complex infrastructure deployment and management overhead, make legacy blockchains a less viable solution to share data in real time.

Advantages

  • Greater reliability
  • New application and business model creation support
  • 24/7 availability

Disadvantages

  • Complexity in sending data to/from the blockchain system
  • Limited scalability
  • Inadequate data security
  • Expensive to develop and maintain

NOTE: Some organizations might also consider streaming data an approach to data sharing. It’s core advantage is making large-scale data available, but there are significant disadvantages like not knowing what's in the data and having "piles" of data to parse through for insights.

Vendia combines the "best of breed" from each type for a new solution

Real-time data sharing solutions are versatile, but to unlock maximum value, they should support you in adding multiple business partners to a value chain. When multi-party data sharing occurs, companies have to come together in a data alliance and share their bits with other involved parties deliberately and in a controlled manner.

Built on an enterprise-grade blockchain as a data exchange platform, Vendia Share is a reliable real-time data sharing solution that allows access to every partner in your permission network and delivers a single source of truth that is both transparent and secured by design.

Every participant receives an access point (a node) to read, write, and view every data point, transaction, or file you make available to other data alliance partners or vice versa. They can also easily connect their on-premise or cloud systems to Vendia without having to build (or maintain) multiple API connection points.

Here’s how Vendia brings the key value, without the complexity, of each of the other data sharing methods:

  • AI/iPaaS – Vendia also allows for each application to independently interface through the API layer therefore reducing the need for application-to-application integrations.
  • ERP – Vendia provides data availability to each independent silo through use of distributed data in nodes, each with an accurate current state of data and all changes made over time (in the ledger)
  • Public cloud platforms – Built on the leading CSPs, Vendia provides scalability, high reliability, and availability that the cloud platforms offers, while also providing stronger resiliency with supercloud data sharing
  • Conventional data lake – Vendia allows for sharing of both scalar and file data, emulating the flexibility of a data lake without being beholden to a single cloud’s solution
  • Legacy blockchains – Vendia provides the immutability, availability, and reliability of legacy blockchains while also providing scalability with cloud infrastructure and use case applicability with schema definition and API availability — we call it next-gen blockchain or business blockchain

New data stored gets replicated at high speed so all permissioned partners can see the data they’re supposed to in real time. Meanwhile, a built-in consensus mechanism resolves potential conflicts to ensure superior data accuracy. Vendia Share also automatically generates API (GraphQL-based) for admin operations, CRUD operations, and smart contract consideration and execution.

With Vendia connecting partners with ease and eliminating the need for ongoing maintenance, you can focus on what matters most to your company, your partners, and your customers.

Accelerate your growth with Vendia Share

Your organization's data ecosystem today will drive innovation tomorrow. If you’re ready to explore and leverage real-time data sharing to accelerate your business’s growth, try the app for free or contact our team.

We’ll help you find the right real-time data sharing solution and can get you started with a one-week proof of concept.