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ML & AI Data Analytics Solutions
Build, Train, and Deploy Models Faster with Open-Source Scalability
TeraDB Cloud empowers ML engineers and data scientists to process petabytes of training data, serve real-time inferences, and manage AI workflows—all on a cost-effective, open-source stack.
Key Challenges in ML & AI Data Analytics
Data Volume & Velocity
Processing high-frequency IoT/sensor data or log streams for training.
Feature Engineering Bottlenecks
Slow feature stores delay model iteration cycles.
Real-Time Inference Latency
Scaling inference endpoints for millions of requests without degrading performance.
Costly Experimentation
Training models on large datasets becomes prohibitively expensive.
Model Governance
Tracking lineage, versions, and compliance (GDPR, HIPAA) for production models.
Unstructured and Uncompressed Data
Different Data Sources provide data in unstructured or Uncompressed form.
Technical Use Cases for ML & AI
Real-Time Feature Stores
Challenge
Serve low-latency features (e.g., user embeddings, session counts) to online models.
Solution
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Build a ClickHouse-powered feature store with time-windowed aggregations (e.g., 1-minute user engagement metrics).
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Cache hot features in RediSearch for <5ms retrieval (integrated with RedisVL for vector similarity).
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Sync features to ElasticSearch for hybrid search (text + vectors) in recommendation systems.
Distributed Model Training
Challenge
Train deep learning models on 100TB+ datasets without moving data.
Solution
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Use ClickHouse’s S3/HDFS integration to train PyTorch/TensorFlow models directly on stored data.
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Leverage GPU-accelerated ClickHouse instances (AWS p3/GCP A2) for 10x faster embeddings.
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Track experiments with MLflow integration and log metrics to ClickHouse.
Real-Time Anomaly Detection
Challenge
Detect fraud, defects, or outages in streaming data (e.g., payments, IoT sensors).
Solution
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Ingest Kafka streams into ClickHouse, compute statistical baselines (Z-scores, MAD) with SQL-based window functions.
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Deploy PyTorch models as ClickHouse ML UDFs for real-time scoring.
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Trigger alerts via ElasticSearch’s alerting plugins and push to PagerDuty/Slack.
Personalized Recommendations
Challenge
Serve 100K+ personalized recommendations/sec with <50ms latency.
Solution
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Store user-item interactions in ClickHouse for fast cohort analysis (e.g., “users who bought X”).
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Generate embeddings with ClickHouse ML and index them in RediSearch for vector similarity searches.
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A/B test models using ElasticSearch’s ranking evaluation tools.
AI-Powered Search
Challenge
Combine keyword and semantic search for e-commerce or content platforms.
Solution
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Use ElasticSearch’s dense vector plugin for hybrid search (BM25 + HNSW).
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Precompute query embeddings with ClickHouse ML and cache results in RediSearch.
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Fine-tune models using ClickHouse logs to improve relevance.
How TeraDB Cloud Solves ML & AI Challenges
Speed & Scale
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ClickHouse: Process 100K+ events/sec for real-time feature engineering.
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ElasticSearch: Hybrid search at scale (text + vectors).
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RediSearch: Sub-millisecond feature/vector caching.
Cost Efficiency
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Spot Instances: Train models on AWS Spot/GCP Preemptible VMs (40-50% cost savings).
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BYOC (Bring Your Own Cloud): Use reserved instances or on-prem GPUs for training.
End-to-End Pipelines
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Prebuilt Airflow/Kubeflow Connectors: Orchestrate data prep → training → deployment.
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ML Observability: Monitor drift/accuracy with Grafana dashboards.
Security & Compliance
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BYOK (Bring Your Own Key): Encrypt training data and model artifacts with your KMS.
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RBAC: Restrict access to sensitive datasets (e.g., PII in training logs).
Expert Support
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ClickHouse ML Engineers: Optimize SQL queries for feature engineering.
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ElasticSearch NLP Specialists: Fine-tune semantic search pipelines.
Compressed and Structured Data Storage
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Compress data up to 90% for less storage cost.
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Structure data at ingestion to minimise the query execution time.
Managed Services with Random Product Feature’s
Managed ClickHouse Services
Supercharge real-time analytics with a fully managed columnar database. Process petabytes of data at lightning speed, backed by automated scaling, security, and 24/7 expert support.
Managed Apache Kafka Services
Build fault-tolerant data pipelines with a fully managed Kafka service. Stream thousands of events per second, powered by auto-scaling brokers, geo-replication, and enterprise security.
Managed ElasticSearch Services
Deliver millisecond search & analytics with a managed ElasticSearch solution. Automate indexing, security, and compliance for log analytics, APM, or customer-facing search.
Managed Redis Services
Power real-time apps with a fully managed Redis service. Achieve microsecond latency for caching, leaderboards, and pub/sub messaging, backed by instant failover and TLS encryption.
What Our Clients Are Saying
Hear from industry leaders who have transformed their data infrastructure with TeraDB Cloud.
Michael Johnson
Runs Data Devision
“TeraDB Cloud’s real-time fraud detection system saved us individuals hundreds of thousands of dollars in possible losses. Their handled RediSearch services were essential to our achievement.”
Sophia Chen
VP of Engineering
“With the scalable infrastructure of TeraDB Cloud, we lowered latency for our gaming analytic system from 2 seconds to less than 200ms.”
Steve Preusz
Data Science Lead
“Using TeraDB Cloud, we established a completely managed healthcare data analysis pipeline.” At every point, their committed support staff guaranteed conformity and safety.”
James O’Neil
Senior Data Engineer
“In our pipelines, the smooth integration of Kafka and Elasticsearch has been revolutionary. Experts with TeraDBCloud will make sure there is no downtime throughout migration.”