ACIntegration · Operations and Data

Connect Apache Cassandra data to Salesforce Agentforce

Apache Cassandra is the highly available, linearly scalable wide-column database used to store time-series data, event logs, IoT telemetry, and high-write application data at scale — where traditional relational databases cannot sustain the write throughput or the storage volume the use case requires. For organisations operating IoT platforms, telemetry pipelines, high-frequency transaction systems, or large-scale event logging applications, Cassandra holds the time-ordered data that represents the operational history of customer systems. This historical data is commercially relevant: the device telemetry that signals a hardware issue before the customer notices, the transaction event log that provides the audit trail for a billing dispute, the time-series metrics that reveal a performance degradation pattern. When Emerge Digital connects Cassandra to Agentforce, time-series and event data stored in Cassandra is available to agents during service and commercial conversations — and Salesforce commercial events can coordinate with Cassandra-backed application workflows.

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What this unlocks

Time-series event history for service and account conversations: when a customer reports a performance issue or service degradation, an agent can query the Cassandra event log or metrics time-series for the customer's account over the relevant period — retrieving the sequence of events or metric readings that characterise the issue in detail, rather than relying on summarised data from the reporting layer.
IoT device telemetry context for field service and support: organisations operating IoT platforms store device telemetry in Cassandra at high frequency — when a customer contacts support about a device failure or anomaly, an agent can query the Cassandra telemetry table for the specific device identifiers associated with the customer, retrieving the recent sensor readings, event codes, and connectivity status that inform the diagnosis.
High-volume transaction audit trail for billing and compliance conversations: financial services and high-frequency transaction platforms store audit-grade transaction records in Cassandra because relational databases cannot sustain the write volume. When a customer queries a transaction record, an agent can query the Cassandra transaction log table using the customer's identifier and the transaction date range, returning the precise record without routing the query to the operational reporting database.
Salesforce account events coordinate with Cassandra application state: when a Salesforce opportunity closes, a service tier changes, or an account is provisioned, an Agentforce agent can write a coordination record to the Cassandra application state table — updating the entitlement configuration or provisioning state in the Cassandra-backed application without a manual engineering step or a batch synchronisation delay.

In the customer journey

Device telemetry history surfaces in a field service case

An enterprise IoT customer reports that three sensors in a production facility have been returning anomalous readings for two days. The agent queries the Cassandra telemetry table for the three device identifiers associated with the customer's facility, reading the last 72 hours of sensor readings. The query returns a pattern: the anomaly began at the same timestamp across all three devices, coinciding with a network event logged in a separate Cassandra table. The field service engineer is dispatched with the specific device IDs, the anomaly start time, and the correlated network event — significantly reducing the on-site diagnosis time.

Transaction audit log resolves a billing dispute

An enterprise customer disputes a charge for 12,000 API calls in a single day, claiming their system could not have generated that volume. The agent queries the Cassandra transaction log table for the customer's API key over the disputed date — the query returns 11,847 records with timestamps distributed across a six-hour window, matching a scheduled data import job. The agent surfaces the transaction timestamps and endpoint data to the customer, confirming the call volume corresponds to the import job. The dispute is resolved without an engineering team query.

Performance metric time-series reveals degradation pattern before escalation

A customer contacts support reporting that their application has been slower than usual for three days. The agent queries the Cassandra metrics time-series for the customer's cluster identifiers over the past 96 hours — the query returns a gradual throughput degradation pattern that began when a new data partition strategy was applied. The pattern is consistent with a known Cassandra partition hotspot condition. The support engineer has the specific diagnosis before the customer escalates to a P1 incident.

Why not querying Cassandra through the application API?

Application APIs expose processed, aggregated data appropriate for customer-facing features. Raw time-series telemetry, audit-grade transaction logs, and detailed event sequences are typically not exposed through the application API because the volume and granularity are intended for internal operational use. A service agent diagnosing a specific device anomaly or a billing auditor verifying a transaction record needs the raw Cassandra data — the specific timestamps, the sequence of readings, the granular event records — not a summary response from the application API. Emerge Digital builds the governed read layer that gives Agentforce agents query access to the specific Cassandra tables and partition key ranges relevant to each commercial or service use case.

Cassandra's Agentforce integration is most valuable for organisations where Cassandra holds the high-volume, time-ordered data that represents customer operational history — IoT telemetry, transaction logs, event streams, metrics time-series — and where access to that raw historical data would materially improve the quality of service and commercial conversations. It complements the operational database integrations (Cosmos DB, DynamoDB) for use cases where Cassandra's write-throughput and time-series access patterns are the reason it was chosen.

How Emerge integrates Apache Cassandra

Emerge Digital connects Apache Cassandra to Salesforce Agentforce as a consulting engagement. We identify which Cassandra keyspaces and tables contain commercially relevant data, design the partition key strategy for agent queries that ensures time-bounded lookups rather than full table scans, configure the read-only agent access layer with appropriate query rate governance, and integrate the Cassandra data into service and commercial Agentforce workflows. The integration is designed around your Cassandra data model and your Salesforce service model.

How we structure an engagement

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FAQ

Cassandra is designed for specific partition key access patterns — can agents run flexible queries?

Agent queries are designed around Cassandra's partition key model — they query by the customer identifier, device identifier, or account key that anchors the partition, within a time range, rather than running unpartitioned queries that would scan the entire table. The integration design includes a review of the Cassandra data model to ensure agent query patterns are compatible with the existing partition strategy.

We use DataStax Enterprise or Astra DB (managed Cassandra) rather than open-source Cassandra — does the integration work?

Yes. The integration is compatible with open-source Apache Cassandra, DataStax Enterprise, and Astra DB (DataStax's managed Cassandra service). The Cassandra Query Language (CQL) API is consistent across deployments; the connection and authentication configuration differs by deployment type.

Can the agent write to Cassandra — update a configuration record or mark an event as processed?

Specific pre-approved write operations — like writing a coordination record when a Salesforce opportunity closes — can be configured with defined partition key scope and authorisation requirements. General-purpose Cassandra writes by agents require an engineering team approval step for each write pattern to ensure writes are partition-key-aligned and do not introduce hotspot conditions.

How long does a Cassandra + Agentforce integration take?

A focused engagement typically runs five to seven weeks: reviewing the Cassandra data model to identify partition key-compatible agent query patterns, designing the read-only access layer with query rate governance, configuring Salesforce action triggers for coordination writes, and testing time-series retrieval, telemetry queries, and audit trail scenarios under realistic partition load.

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Tell us what your agents need to read and write in Apache Cassandra, and we'll design the integration and the governance around it.

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