CDR Processing & Network Operations
Database Services for Telecom & Network Operators
Carrier-grade telecom data layers demand high-volume CDR ingestion (often 100K+ writes/sec at peak), sub-millisecond in-memory prepaid balance rating, and five-nines availability targets for core databases. Retaining dedicated telecom DBRE over generic cloud DBAs adds partitioned time-series storage, atomic Lua-scripted balance reservations, automated multi-region failover, and incident response on agreed initial-response targets.
Process billions of CDRs, run real-time billing at telecom scale, and manage millions of subscriber records on databases designed for carrier-grade availability. We bring that reliability engineering to your data infrastructure.
Telecom database problems — sound familiar?
- ▸ CDR ingest pipeline — millions of call / data-session records per minute have to land in Cassandra / ClickHouse for billing reconciliation and fraud-detection; ingest backs up during peak hours and the downstream BSS jobs miss their SLAs.
- ▸ Subscriber-profile lookup latency — every network signalling event needs sub-10ms profile lookup; the HSS / HLR adjacent DB (often Aerospike or Cassandra) needs hot-key analysis and capacity rebalancing.
- ▸ 5G data-plane integration — UPF / SMF telemetry and CHF charging events are landing on the OLAP path concurrently with the legacy 4G CDR pipeline; the consolidated billing data warehouse plan has not been sized for the joined load.
JusDB telecom database team: CDR ingest pipelines, subscriber-DB hot-key tuning, 5G + 4G consolidated billing architecture. Book a telecom database scoping call →
Why Do Telecom Operators Choose JusDB?
Telecom databases process billions of events daily, require five-nines availability, and must handle real-time billing with zero revenue leakage. Our DBAs understand the unique demands of carrier-grade operations.
Massive Throughput
CDR ingestion pipelines sized for 100K+ records/second peaks, with time-series optimized storage and automatic data lifecycle management.
Network Analytics
Real-time network performance queries across cell towers, traffic patterns, and QoS metrics for capacity planning.
Carrier-Grade HA
Synchronous replication, automated failover built for an RPO of zero, and rolling maintenance procedures, designed for five-nines availability targets.
Real-Time Billing
Sub-millisecond balance lookups and atomic rating operations for prepaid and postpaid subscriber management.
What Is Included in Our Telecom Database Services?
CDR Processing & Mediation
- High-throughput CDR ingestion sized for 100K+ writes/sec peaks
- Time-series partitioning with automatic data tiering
- Mediation pipeline optimization for rating accuracy
Billing & Revenue Assurance
- Real-time prepaid balance management with Redis
- Postpaid billing aggregation with ACID guarantees
- Revenue leakage detection and reconciliation queries
Subscriber Management
- Million-subscriber profile optimization
- Provisioning and entitlement database design
- Self-service portal query performance tuning
Network Analytics & 5G
- Cell tower performance time-series analytics
- QoS metric dashboards and capacity planning
- 5G network slice data management
Which Database Engines Power Telecom Operations?
From CDR ingestion to real-time billing, we optimize the right engine for each telecom workload.
PostgreSQL
Subscriber management, billing ledgers, provisioning, and complex rating queries with full ACID compliance.
Cassandra / ScyllaDB
CDR ingestion at massive scale, network telemetry, time-series cell tower analytics, and event logging.
Redis / Valkey
Real-time prepaid balance caching, session state, rate limiting, and pub/sub for network event notifications.
MySQL / MariaDB
CRM systems, order management, trouble ticketing, and self-service portal backends with replication.
Elasticsearch
CDR search, network log analysis, fraud detection pattern matching, and operational dashboards.
MongoDB
Flexible network configuration documents, device profiles, and dynamic plan/offer catalogs.
How Does JusDB Deliver Carrier-Grade Database Reliability?
Telecom systems demand the highest availability standards in any industry. We design every layer for five-nines availability targets and guard billing paths against revenue leakage.
- 01
Synchronous Replication
Replication across availability zones built for an RPO of zero, with automated failover detection tuned and timed in failover drills.
- 02
Rolling Maintenance
Database patches, upgrades, and schema changes applied with rolling and blue-green deployment patterns to avoid service interruption.
- 03
Data Lifecycle Automation
CDRs and network logs automatically tiered from hot to cold storage, so aging records move off the most expensive infrastructure.
- 04
Capacity Forecasting
Predictive analytics on CDR volumes, subscriber growth, and network expansion to provision ahead of demand.
Telecom Database Support
Networks never sleep, so choose the coverage your operations need. Our engineering team is in India (IST, UTC+5:30). Business-hours coverage is Mon–Fri 09:00–18:00 IST.
- NOC-integrated monitoring with real-time alerting on CDR processing delays, billing anomalies, and replication health.
- Change management with pre-approved maintenance windows and mandatory rollback procedures.
- Initial-response targets for critical incidents such as billing outages, CDR pipeline failures, or subscriber database degradation: 2 to 4 hours in covered business hours; 15 minutes for P1 incidents with 24x7 on-call. Targets, not resolution guarantees.
Illustrative Scenarios
Telecom Engagement Scenarios
Example engagements and what each one measures, not client results. Results depend on the workload; we baseline before and measure after each approved change.
See what named clients sayMobile Network Operator
Move CDR processing from Oracle to Cassandra and tier older records to cheaper storage.
What we measure
- Daily CDR ingest volume
- Query latency before and after
- Storage cost per month
MVNO Platform
Build real-time prepaid billing on Redis and PostgreSQL with atomic balance reservations.
What we measure
- Balance-check latency (p99)
- Gaps between cache and ledger
- Throughput at peak rating load
Fiber ISP
Tune a subscriber management database and run schema migrations online instead of in maintenance windows.
What we measure
- Subscriber lookup latency
- Lock waits during migrations
- Availability against the agreed target
How JusDB Telecom DBRE compares to alternative models.
Carrier-grade telecom infrastructure requires high-volume CDR ingestion, sub-millisecond prepaid rating, and strict five-nines availability targets. Compare JusDB dedicated Telecom DBRE against generic cloud DBAs and in-house engineering teams.
| Telecommunications Vector | JusDB Telecom DBRE | Generic Cloud DBA | In-House Engineering |
|---|---|---|---|
| High-Throughput CDR Ingestion (100K+ writes/sec) | Partitioned time-series tables (TimescaleDB / ScyllaDB append logs), memory-ring write buffers (Kafka/Vector), and bulk copy pipelines sized for 100K+ CDR writes/sec, designed to avoid dropped records and write-lock stalls. | Stores CDR streams in monolithic cloud databases with default WAL flush parameters; commits encounter severe disk I/O wait queues and transaction stalling during peak network call windows. | Direct synchronous application-to-database inserts without streaming ingestion queues; sudden call bursts saturate connection pools and trigger unrecoverable CDR billing event losses. |
| Real-Time Balance Rating & Prepaid Deductions | In-memory distributed key-value state tiers (Aerospike/Valkey) for sub-millisecond rating lookups, atomic Lua script balance reservation tokens, and asynchronous reconciliation ledgers. | Relies on standard relational database row locking (SELECT ... FOR UPDATE) for balance checks; high concurrent SMS and voice calls trigger severe lock contention and rating timeouts. | Check-then-act balance validation in application services without distributed lock coordination; network latency spikes cause race conditions and negative prepaid account balances. |
| Carrier-Grade Availability Engineering | Synchronous multi-datacenter active-active clustering, rolling engine upgrades, Patroni DCS quorum orchestration, and automated failover with RTO measured in drills; the availability commitment is set in your service agreement. | Standard cloud multi-AZ failovers with 60–120s DNS propagation delays; network switches encounter transient database disconnects that disrupt active call session routing. | Manual primary-standby failover runbooks requiring NOC engineer escalation and approval; outages result in 30–60 minutes of unbillable voice and data traffic. |
| Subscriber Catalog & Entitlement Query Performance | Optimized composite B-tree and covering indexes for MSISDN/IMSI lookups, in-memory read-through caching for roaming profile entitlements, and p99 lookup latency baselined and tracked per change. | Basic single-column indexes on massive subscriber tables; complex multi-plan discount queries cause sequential table scans and slow down customer portal and provisioning systems. | Unpartitioned subscriber tables with hundreds of columns; MVCC table bloat from frequent status updates degrades lookup performance across billing cycles. |
| Automated CDR Hot/Warm/Cold Storage Tiering | Automated data lifecycle management migrating aged CDRs from NVMe hot storage to compressed columnar warm tiers (ClickHouse/Parquet) and cold S3/GCS archival, lowering storage costs while keeping records available for regulatory retention. | Keeps years of CDR records on expensive cloud block storage (EBS gp3/io2), continuously increasing infrastructure spend without automated compaction or compliance archival. | Ad-hoc SQL DELETE scripts run during maintenance windows; deletes bloat transaction logs, trigger table locks, and leave orphaned records that fail regulatory audits. |
| Network Operations Center (NOC) DBRE Bridge | Senior DBREs on carrier NOC bridges under agreed initial-response targets (24x7 on-call available); real-time CDR drop alerting, automated query anomaly remediation, and carrier-grade change discipline. | Standard 1–4 hour ticket response times through generic support queues with zero telecommunications domain expertise or carrier regulatory context. | Overburdened internal network engineers attempting database triage during major network routing incidents without specialized database performance tools. |
Sev-1 Telecom Database Failure Modes We Intervene Against
Ingestion queue dropouts, balance desynchronization, and subscriber table bloat create severe regulatory liabilities and unbilled network traffic. Our on-call DBREs intervene against these critical production failure modes, starting within your agreement's initial-response target:
Ingestion Queue Spillover Leading to Lost Call Detail Records
Massive call event spikes exhaust unbuffered synchronous database write connections. Disk I/O bottlenecks cause replication worker lag, buffer overflows, and irreversible dropped CDR revenue events.
JusDB DBREs deploy distributed Kafka/Vector memory-ring buffers, implement partition-keyed TimescaleDB/ScyllaDB append tables, and calibrate bulk write pipelines to absorb peak CDR rates without dropping records.
Prepaid Rating Desynchronization Between In-Memory Cache and Ledger
Concurrent subscriber voice and data usage triggers out-of-order balance deductions between Redis cache and the primary PostgreSQL ledger. Read Committed race conditions cause negative account balances and unbilled usage.
We enforce atomic Redis Lua reservation scripts with decrement tokens, deploy PostgreSQL serializable isolation on ledger tables, and maintain a CDC transactional stream reconciling cache states within sub-second intervals.
MVCC Autovacuum Starvation on Rapidly-Updated SIM Status Tables
Continuous network attachment and roaming updates generate millions of dead tuples per hour on subscriber status tables. Default autovacuum parameters fail to keep pace, causing massive index bloat and multi-second subscriber authentication lookups.
We configure aggressive table-level autovacuum settings (scale_factor=0.01, autovacuum_vacuum_cost_limit=2000), schedule non-blocking pg_repack maintenance windows, and cache roaming entitlements in Valkey/Redis for low-latency lookups.
Our DBREs run non-blocking telemetry diagnostics during carrier traffic surges and billing cutoffs to isolate contention without adding query wait states:
Identifies dead tuple accumulation and vacuum lag on high-churn MSISDN subscriber tables and SIM entitlement catalogs.
-- 1. Inspect dead tuples and autovacuum performance on subscriber status tables
SELECT relname, n_live_tup, n_dead_tup,
round(100.0 * n_dead_tup / nullif(n_live_tup + n_dead_tup, 0), 2) AS dead_pct,
last_vacuum, last_autovacuum
FROM pg_stat_user_tables
WHERE relname LIKE %subscriber% OR relname LIKE %sim% OR relname LIKE %device%
ORDER BY n_dead_tup DESC LIMIT 5;
-- 2. Inspect active long-running subscriber balance transactions
SELECT pid, now() - xact_start AS xact_duration, state, query
FROM pg_stat_activity
WHERE state != idle AND xact_start IS NOT NULL
ORDER BY xact_duration DESC LIMIT 5;Tracks real-time insert rates, write amplification, and buffer cache efficiency across active CDR partition chunks.
-- 1. Inspect CDR hypertable chunk insert velocity and tuple insertions
SELECT relname, n_tup_ins, n_tup_upd, n_tup_del,
pg_size_pretty(pg_total_relation_size(relid)) AS total_size
FROM pg_stat_user_tables
WHERE relname LIKE %cdr% OR relname LIKE %call_record%
ORDER BY n_tup_ins DESC LIMIT 5;
-- 2. Inspect background buffer writer performance and dirty page flushes
SELECT buffers_checkpoint, buffers_clean, maxwritten_clean,
buffers_backend, buffers_alloc
FROM pg_stat_bgwriter;Frequently Asked Questions
Ready for Carrier-Grade Database Reliability?
Process billions of CDRs, run real-time billing, and design for five-nines availability with expert telecom database management.