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Data Infrastructure

Aerospike

Real-time NoSQL database built for low-latency, high-throughput workloads

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About Aerospike

Aerospike develops a distributed, multi-model NoSQL database designed for sub-millisecond reads and writes at large scale. It adds graph and vector search capabilities for real-time AI and fraud use cases. Customers are mainly large enterprises in adtech, financial services and telecom.

Common use cases

  • Fraud detection
  • Ad targeting and bidding
  • Real-time personalization
  • Session and profile stores
  • Payments and risk scoring

Social listening

What people are saying about Aerospike

Reviewers value Aerospike's low latency, easy scaling and operational stability, and buyers typically plan for developer tooling, documentation and replication setup.

What stands out

  • Low latency and high throughput are frequently mentioned, especially on SSD-backed deployments.
  • Scaling out and adding nodes is described as straightforward, with built-in sharding and simple high availability.
  • Reviewers report fewer servers needed for similar workloads, which lowers hardware and management cost.

Things to consider

  • Teams typically plan for command-line tooling, since there is no developer GUI for experimentation.
  • Worth confirming documentation and community resources for the specific products in scope.
  • Plan for extra integrity checks when setting up cross-datacenter replication, and confirm query-language fit.

Often compared with: ScyllaDB, Cassandra, Redis, Couchbase

Sources (2)

Themes summarized from public reviews, community discussion and press coverage as of November 2026. They reflect public discussion, not a rating or an endorsement by AI Connect.

Products and services

Aerospike Database

Distributed key-value and document database for real-time workloads.

Aerospike Graph

Graph database service built on the core engine.

Aerospike Vector Search

Vector indexing for AI and similarity retrieval.

Aerospike Cloud

Managed database service.

Pricing and editions. Some reviewers would like lower pricing.

Key features

  • Sub-millisecond latency
  • Hybrid memory architecture
  • Multi-model data
  • Cross-datacenter replication
  • Vector search
  • Strong consistency option

Integrations

  • Apache Spark
  • Kafka
  • Pulsar
  • Presto/Trino
  • Elasticsearch
  • Kubernetes

Aerospike alternatives

FAQs

What is it best for?

Latency-sensitive, high-throughput workloads such as fraud detection and ad serving.

Does it support AI use cases?

Yes, it offers vector search and graph capabilities alongside the core database.

How can it be deployed?

Self-managed on-premises or in cloud, or as a managed cloud service.

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