Transform your data strategy with RaptorDB Pro - Text

Anubhav P · yesterday

RaptorDB Pro: where work happens is where insight should live

A data strategy, not a database upgrade.

For decades, enterprises have split their data into two worlds — one for running the business, one for understanding it. RaptorDB Pro is built to close that gap, bringing operational and analytical data together inside the Now Platform. The real question it answers isn't "is it faster?" It's whether your data architecture will enable or constrain your data strategy over the next three to five years.

The great data divide

On one side sits operations — the systems where work gets done. On the other sits analytics — the systems where organizations make sense of it all. Between them, enterprises have built countless bridges: integration tools, custom code, and ETL pipelines moving data from one side to the other.

Those bridges turned out to be one-way streets. Data flows out to be analyzed, but the resulting insight rarely makes it back to the point of action in time to matter. By the time a dashboard reflects reality, the incidents have been resolved, the change has shipped, and the opportunity has passed.

As AI raises the stakes — and the volume — that divide becomes the single biggest constraint on what an organization can do with its data. AI models trained on stale extracts produce stale recommendations. Agents that can't query live operational state can't act on it. The divide that was a reporting inconvenience becomes an AI bottleneck.

Does your data strategy solve core business challenges?

When data leaders talk about strategy, the ambitions tend to land in four places. Each one is held back by the same divide.

Enabling analytics where work happens

The outcome of analytics is action, not observation. Real-time decision support requires self-service, ad hoc analytics capabilities integrated with the system of action — not a separate system updated overnight.

What gets in the way: Analytics is done in a separate system. New insights require project work. Different teams live in different tools, on top of copied datasets. Difficult to close the loop for real-time decision support.

How RaptorDB Pro addresses it: RaptorDB Pro is an HTAP database, supporting operational and analytical workloads, long-term data retention, and investigations from first- and third-party tools.

Reducing IT costs

Data duplication is expensive to build and maintain. Maintaining separate operational and analytical systems compounds costs — every pipeline is something to build, monitor, and fix when it breaks.

What gets in the way: Operational and analytical operations run on separate systems. Building and maintaining ETL pipelines. Data management is already a challenge before adding analytical workloads on top.

How RaptorDB Pro addresses it: RaptorDB Pro avoids costs associated with external warehouses or lakes, including custom tooling, middleware for ETL pipelines, and development time.

Managing data as AI scales up

Agentic and autonomous solutions require data unity. Fragmentation and performance bottlenecks lead to opportunity costs that lower the benefits of AI deployments. Every AI strategy requires a rock-solid data strategy underneath it.

What gets in the way: Data fragmentation has significant impacts on AI deployments. Every AI strategy requires a rock-solid data foundation that most organizations haven't built yet.

How RaptorDB Pro addresses it: RaptorDB Pro delivers large-scale data retention and analysis of contextualized data. Retaining data context is foundational to an AI-ready data strategy.

Minimizing data security exposure

Workflows contain sensitive data about your operations, clients, partners, and employees. Duplicating this data across systems increases security exposure — ACLs defined in ServiceNow don't follow the data when it leaves.

What gets in the way: Extensive effort is done to implement access controls in ServiceNow. ACLs and context are not preserved when data is copied out.

How RaptorDB Pro addresses it: RaptorDB Pro eliminates the need to duplicate data to analytical systems. This decreases security exposure and risk of undesired data access.

How RaptorDB Pro's capabilities fit together

At its core, RaptorDB Pro is an HTAP database — it processes transactional and analytical queries concurrently, so teams run reports and complex queries without impacting operational users and agents. Three capabilities build on that foundation and work together as one system.

Live Perform

Live Perform is the HTAP engine inside RaptorDB Pro — Column Store Index plus Parallel Query Processing. The Column Store Index automatically indexes and compresses your largest datasets so each query reads and processes only the relevant data instead of scanning all of it — the basis for analytics that run up to 27x faster. Parallel Query Processing lets the database run analytics on larger datasets without slowing down concurrent operational work, adding headroom for more applications, data, and users as the business scales.

Live Connect (SQL API)

Direct Bring-Your-Own-BI and data-lake integration. Standard JDBC/ODBC protocols connect any tool — Power BI, Tableau, Excel, DBeaver, Looker — to ServiceNow data with a zero-copy architecture: data stays in ServiceNow while external tools query and visualize it securely, with full ACL enforcement. No extraction pipeline, no separate copy to govern, no staleness.

Live Archive (Data Archiving)

An object store for scalable online archiving that keeps historical data warm for seamless querying alongside current data. Archived records are compressed by up to 50% while remaining fully governed and queryable via the same interface — relevant for trend analysis, time-series reporting, and compliance use cases where multi-year history matters.

Together, these capabilities deliver: real-time analysis on live data without data movement; trend analysis and time-series reporting on warm archived data; ACLs and governance controls enforced on every query; historical records retained at lower cost — accurate, trusted, responsive dashboards at a lower total cost of ownership.

RaptorDB Pro is foundational to the data strategy

The four outcomes resolve into the same architecture — and each stakeholder group gets what they need from a single governed system.

For the Chief Data / Information Officer: a single governed store that serves both operational and analytical queries. No more reconciling two copies of the truth. Real-time analysis on live data without data movement, and trend analysis on warm archived data when historical depth matters.

For the corporate analyst: a live SQL endpoint that connects directly to any standard BI tool. Write a query, get current results. Build a dashboard against live data, not a nightly extract. Accurate, trusted, responsive dashboards — without waiting for a data engineering team to build or maintain a pipeline.

For the security and governance officer: all data stays inside the Now Platform's governance boundary. ACLs defined once, enforced everywhere — on every query, whether it comes from a ServiceNow report, a Power BI dashboard, or a SQL client. No exports, no replicas, no separate access control surface to audit.

The real decision

Evolving from optimizing around your constraints to removing those constraints entirely.

Current Approach	RaptorDB Pro Approach
Analytics require extracting and duplicating data outside ServiceNow	Zero ETL analytics — live, historical, and intraday insights in one system
Performance tuning becomes a continuous balancing act as data grows	Scale and new use cases are validated before becoming business risk
Governance is enforced after the fact across disconnected systems	Compliance, security, and analytics share a single source of truth
Growth initiatives move cautiously, constrained by platform limits	Teams focus on outcomes and innovation, not data movement and workarounds
Not ready for agentic AI data growth	Ready for agentic AI data growth

The question isn't "is RaptorDB Pro faster?" The question is: will your data architecture enable or constrain your data strategy ambitions over the next three to five years?

Speed solves today's problems. Architecture determines tomorrow's outcomes.

Do you want to manage limits — or eliminate them?