Datasparc Delivers Fast and Secure Access to Databases Hosted On-Prem or in the Cloud

Datasparc Delivers Fast And Secure Access To Databases

TL; DR: Datasparc, headquartered in San Diego, CA, delivers secure data management solutions compatible with SQL and NoSQL databases hosted on-premises or in the cloud. The company’s flagship product, DBHawk, provides intuitive and innovative tools for accessing, integrating, developing, and analyzing data. Datasparc’s object access control, support for data masking, and data-auditing capabilities make it an ideal choice for organizations that must comply with data privacy regulations. Moving forward, artificial intelligence (AI) and machine learning (ML) will be added to the platform to help customers further streamline workflows.

Data analytics and business intelligence have become mission-critical for many businesses — and for good reason. Whether it’s used to help generate revenue, ensure regulatory compliance, or support strategic processes, data plays an essential role in business growth.

It follows that processes that obstruct or limit access to mission-critical data can result in legal penalties, financial loss, and problems with business continuity.

That’s why many users are turning to easy-to-use, self-service database tools, such as Datasparc, to securely access, integrate, and analyze massive amounts of business-critical data on demand.

Datasparc logo

Datasparc makes it easier to transform data into actionable insight.

“Everyone wants data now — that’s just how this industry is,” said Manish Shah, Founder and CEO of Datasparc. “But without the proper tools in place, businesses have to go through a multi-layered process to access data. It can delay the entire process weeks or even months. With Datasparc, you can access data with security measures in place within 30 minutes.”

Datasparc’s flagship product, DBHawk, grants users quick access to data without compromising on security or privacy. The infrastructure-agnostic platform provides secure access to on-premise and cloud databases. It also supports a range of SQL and NoSQL databases, including AWS Athena, Amazon Redshift, Greenplum, Microsoft SQL Server, MongoDB, MySQL, Oracle, SAP Hana, and Teradata.

Ultimately, Datasparc aims to lead the market for database tools through innovative, user-friendly solutions that help businesses manage data securely. With the help of artificial intelligence (AI) and machine learning (ML) tools currently under development, Datasparc’s web-based BI and database management software is poised to do just that.

Infrastructure-Agnostic, Web-Based Data Management

Manish told us that while businesses have wielded SQL and databases in general as tools for years, the volume of data leveraged today has soared exponentially.

“If you go back 10 or 15 years, a mid to large-sized company would typically only have a single database. If they were an Oracle shop, they would have an Oracle database. If they were a Microsoft shop, they would have a Microsoft database,” he said. “Now, the amount of data has scaled so much that businesses everywhere work with many databases as required to suit their needs.”

As proof, Manish pointed to DB-Engines, a knowledge base of relational and NoSQL databases. In addition to established relational systems, the site emphasizes the growing rate of NoSQL-based solutions. As of November 2020, the DB-Engines Ranking tool accounted for more than 360 unique database systems.

DBHawk logo and text reading "Protect Your Data"

The DBHawk platform provides secure access to SQL and NoSQL databases hosted in the cloud or on-premises.

“On top of that, a lot of companies started shifting some of their infrastructure to the cloud, so they may have a hybrid hosting solution,” Manish said. “At the same time, most of the database query tools on the market use a client-server model, adding to complications, and there is no data security concept.”

As database use has skyrocketed, they’ve unfortunately attracted the attention of hackers hungry for valuable and sensitive information. To fill gaps in both the database tools and security market while solving for complexity, Datasparc created DBHawk.

“We developed this web-based, centralized product where you do not have to install any tool on your machine — it’s web-based access, and you can connect to all kinds of databases, SQL, NoSQL, whether they’re hosted in the cloud or on-prem,” Manish said.

To make things even easier, the company’s DBHawk Query Builder helps users build and create database queries. The technology logs user authentication and SQL activities, providing full auditing capabilities to make regulatory compliance more manageable.

“And when you write queries, we log all your activities, including what query you are writing, when you are connecting, what IP address you are connecting from, etc.,” Manish said. “For data-sensitive companies in the financial, human resources, and healthcare domains, this is very important.”

In addition, DBHawk supports dynamic data masking based on predefined policies. With DBHawk central policy management, administrators can give end-users access to the data they need and nothing else.

A Flexible Yet Focused Customer-Centric Road Map

Manish said Datasparc’s client portfolio consists largely of enterprises with more than 50 users. Other companies have between 500 and 2,000-plus users who all need secure, fast access to various databases hosted on-premises or in the cloud. The Datasparc platform is perfectly scalable and able to accommodate a large number of users.

From an ROI perspective, it’s easy to see how streamlining a traditionally time-consuming process benefits the businesses of Datasparc customers.

“It’s possible to get things done without a platform like ours, but the costs quickly add up: You’ll have to spend more hours, use multiple tools, and involve multiple people,” Manish said. “We remove all those bottlenecks with our tool; it’s very simple and easy.”

DBHawk boasts a long list of features and functionalities, from database security and auditing to management, reporting, and scheduling. And the company is continually improving the product based on an in-depth understanding of the needs of its customers.

The company follows an agile software development approach emphasizing team collaboration, flexibility, adaptive planning, and incremental delivery. Manish said this strategy gives the company the ability to pivot when necessary but also maintain a steady course.

“We have a clear product road map to guide us, but since we support so many databases and so many enterprise-level customers, every customer has unique ideas,” Manish said. “We determine how well each request fits into our product road map, as well as how much value it can bring. If it brings a lot of value to our customers, we will alter our priorities.”

Reduce Manual Configuration Work via Machine Learning

Datasparc’s future plans include integrating AI and ML into DBHawk, a move intended to further streamline data workflows.

“At times, database administrators have to do some manual configurations,” Manish said. “For example, if customer data includes credit card information, the database administrator has to go into our tool and create a policy to manage credit card information. So why not use machine learning?”

That’s precisely what Datasparc is doing with its patent-pending technology, which will allow DBHawk to automatically scan data, identify attributes, and suggest the policies, eliminating manual work and helping harden security measures.

The technology will also help users automate regulatory compliance, making it ideal for organizations that regularly deal with data protection laws such as FISMA, FERPA, GDPR, HIPAA, and PCI.

“Instead of a human proactively figuring things out, DBHawk will be able to process large amounts of data to check for sensitive information,” Manish said. “Instead, the data administrator is the final person saying, ‘Yes, this is exactly what I need.’”

The technology has the potential to transform regulatory compliance as we know it.

“That is the beauty of machine learning and AI,” Manish said. “It helps eliminate human error and save human hours.”

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