Faster signals. Fewer servers. More wins.
Aerospike delivers sub-millisecond latency up to petabyte scale, handles millions of ad requests per second, and reduces infrastructure costs by up to 80%. No tuning marathons. No server sprawl. Just a real-time engine you can drop into your stack and scale with confidence.
Extreme performance, less overhead
Process 10x more queries per node than legacy systems — with lower latency, fewer servers, and no tuning marathons.
Always-on, everywhere
Active-active, geo-distributed architecture delivers sub-ms decisioning and high availability at global scale.
Built for what’s next
Power AI-driven targeting, fraud detection, and privacy-safe activation with real-time profiles and fresh behavioral data.
Trusted by AdTech leaders
See all customer storiesUse the right data model for the right decision
Power every decision with the right data structure — from identity graphs to embeddings — all in one real-time engine.
Core AdTech workloads — powered by Aerospike
Aerospike delivers the speed, scale, and efficiency required to make these foundational AdTech workloads real-time — and revenue-generating.
Real-time bidding
Make millisecond decisions for auctions, optimization, and creative selection — with deterministic speed and 99.99% uptime.
Identity graphs and Customer 360
Link and activate profiles across channels with sub-ms lookup, audience stitching, and real-time identity resolution.
Commerce media and product recommendations
Power high-affinity lookalikes, identity graphs, and personalized recommendations at scale.
Fraud detection and attribution
Ingest and evaluate behavioral signals instantly to detect anomalies, trigger alerts, and support accurate attribution — all with built-in analytics capabilities.
Mobile, CTV, and streaming
Activate high-velocity signals from apps, CTV, and OTT platforms without latency spikes — even during peak concurrency windows.
Retail media and ad serving
Optimize impressions with contextual data and real-time audience matching — across on-site, off-site, and partner networks.
NoSQL databases in AdTech
| Feature/ Criteria |  |
 |
 |
ElastiCache |  |
 |
|---|---|---|---|---|---|---|
| Latency Under Load | Consistent sub-ms P99 | Can spike under RTB loads | High cost in infrastructure and difficult to manage for write-heavy traffic | Great for reads, ok for real-time writes | Sub-ms possible, but not consistent | Latency spikes due to compaction |
| Write Performance | Optimized for high-frequency updates | Scales but throttles under bursty loads | Write speed depends on memory and I/O; sustaining high throughput is difficult at scale. | Extremely fast, but not durable | Good, but tuning-intensive | Suffers from compaction & write stalls |
| Scaling Efficiency | 10x more QPS per node vs others | Auto-scales but gets expensive fast | Complex tuning at scale | Costly and can block scale down | Require more nodes for same throughput | 3-5x more nodes than Aerospike |
| Operational Complexity | Minimal tuning, no compaction, self-healing | Serverless, but limited tuning control | Requires deep tuning past 5TB | Easy to spin up, limited DB capability | Deep tuning required | High ops overhead (tuning, repair, compaction) |
| Architecture | Hybrid memory (DRAM + SSD), active-active, geo-distributed | Serverless with multi-region | Cache + document store hybrid | In-memory, distributed caching with optional replication and sharding. | Shared-nothing model | Peer-to-peer, but ops-heavy |
| Cost Efficiency (TCO) | Up to 80% lower infra cost | Expensive at scale | Less efficient at high scale, infra costs rise with workload growth | Memory-heavy and expensive for persistence | More nodes = more cost | Server sprawl increases infra cost |
| AI/ML & Privacy Readiness | Real-time ML, future-proofed for privacy laws (GDPR, CCPA) | No built-in ML inference or privacy tooling | RecentAI enhancements in the platform | Not applicable | Needs external ML pipeline | No AI/ML native capabilities |
| AdTech Fit | Purpose-built for RTB, CTV, Data Platforms, Fraud detection | Works for AWS-native shops, but costly and inconsistent | Better for hybrid apps, not extreme scale | Read-only cache for ephemeral data | Good throughput, but lacks RTB reliability | Best for batch logging and write-heavy apps, not RTB |
| Best Used For | RTB, Audience Targeting, Data Platforms, CTV, Fraud Detection | Small-to-mid RTB, AWS-native stacks | Hybrid cloud apps with JSON flexibility | Caching (temporary data), not primary DB | Logging, burst writes, mid-scale infra | Large-scale writes, archival workloads |
| Native Graph Support | Yes (User Journey + Product graphs) | No | No | No | No | No |
| Multi-Model One DB | Document, KV, Graph all in one engine | KV and Document | Document, KV, FTS, Analytics in one engine | Key value, Structured Data Types mimic Document | Single-model | Single-model |
| Real-Time Personalization | Embeddings + profiles in same DB | Limited to external ML pipelines | Not native | Not applicable | Batch-oriented | No ANN or embedding support |
| Ideal for Commerce Media | Purpose-built | Costly at scale | Lack graph capabilities | Cache only | Too complex | Lacks real-time personalization |
Built for your role
Whether you're building low-latency pipelines, designing global systems, or optimizing infrastructure at scale — Aerospike is purpose-built for your priorities.
Technical capabilities
Built for speed, scale, and simplicity, Aerospike delivers the core technical capabilities modern AdTech teams need to power real-time decisions — without compromise.
Real-time streaming lookups
Deliver decision-critical data instantly across RTB platforms, exchanges, and user profiles — with sub-ms latency at scale.
Signal aggregation at scale
Hydrate your systems with contextual, viewability, identity, and behavioral data — streamed in milliseconds, not minutes.
Geo-distributed by design
Run active-active clusters across regions, clouds, or hybrid environments with zero-latency handoffs — and 99.99% uptime.
Seamless integration
Use native connectors and SDKs (Python, Java, Go), plus built-in observability (Prometheus, Grafana), to drop into your stack with zero replatforming.
Journey and purchase graphs
Model user paths, ad interactions, and product relationships in real time using built-in graph queries for smarter targeting and optimization.
Testimonials
Senior architects and engineers have learned firsthand how Aerospike's low latency, predictable performance, and operational efficiency have improved their businesses.
Aerospike is Adform’s secret weapon—the enabling data store that allows us to do real-time bidding and make money.
Aerospike is fast, predictable, reliable, and handles large volumes of data, enabling us to provide real-time reporting back to advertisers and giving us an edge over competitors.
Peter Milne
AdformSenior ArchitectWe started doing an evaluation against Cassandra, HBase. Those were the main two ones that we looked at. Postgres pretty much didn’t get consideration because it was getting too expensive. And Aerospike was definitely coming out head-and-shoulders above and with respect to two important parameters…the latency at the 95th percentile…and the throughput that it can sustain.
Sandeep Nawathe
AdobeVP EngineeringThe ability to replicate data across regions is something that Aerospike provides that very (few) other NoSQL databases do with ease. Without Aerospike, we’d be looking for a new NoSQL data store that performs as well as Aerospike does, and I haven’t seen one out there.
Henry Snow
NielsenVP, Infrastructure, Nielsen Marketing CloudWorking with Aerospike has been surprising in some ways because of how easy it is to get started using it and just how simple it is to manage and deal with failures.
Albert Autin
The Trade DeskLead Database Reliability EngineeringOur data demands are growing exponentially, and we need a real-time data platform that can handle our current requirements but ensure that we can adapt and scale for what lies ahead. The Aerospike real-time data platform takes us to the next level in terms of scale and performance and provides us with a standardized platform that ensures our customers can meet the rapid response times they demand both now and in the future.
Diarmuid Gill
Criteo CTOAdditional resources
For a deeper understanding and more insights, explore these additional resources.
- Webinar
Cracking the code: Defeat signal loss in AdTech with graph databases
Signal loss can be detrimental to advertisers who need informative, quality data — see how graph databases can help make signal loss inconsequential. - Blog
Boost Buy-Side AdTech Efficiency with Aerospike's Real-Time Solutions
Unleash the potential of your AdTech with Aerospike's low latency and high throughput solutions, ideal for real-time bidding and data-driven ad strategies. - Blog
The Future of Publisher Monetization in the AI Web
As AI reshapes content consumption, publishers need new tools to protect and monetize their work. Read about a protocol built for the machine-readable web.
Get started with Aerospike
For high-performance, scalable data management and ultra-low latency, ideal for handling massive datasets and real-time applications.
Faster signals. Fewer servers. More wins.
Aerospike delivers sub-millisecond latency up to petabyte scale, handles millions of ad requests per second, and reduces infrastructure costs by up to 80%. No tuning marathons. No server sprawl. Just a real-time engine you can drop into your stack and scale with confidence.
Extreme performance, less overhead
Process 10x more queries per node than legacy systems — with lower latency, fewer servers, and no tuning marathons.
Always-on, everywhere
Active-active, geo-distributed architecture delivers sub-ms decisioning and high availability at global scale.
Built for what’s next
Power AI-driven targeting, fraud detection, and privacy-safe activation with real-time profiles and fresh behavioral data.
Trusted by AdTech leaders
See all customer storiesUse the right data model for the right decision
Power every decision with the right data structure — from identity graphs to embeddings — all in one real-time engine.
Core AdTech workloads — powered by Aerospike
Aerospike delivers the speed, scale, and efficiency required to make these foundational AdTech workloads real-time — and revenue-generating.
Real-time bidding
Make millisecond decisions for auctions, optimization, and creative selection — with deterministic speed and 99.99% uptime.
Identity graphs and Customer 360
Link and activate profiles across channels with sub-ms lookup, audience stitching, and real-time identity resolution.
Commerce media and product recommendations
Power high-affinity lookalikes, identity graphs, and personalized recommendations at scale.
Fraud detection and attribution
Ingest and evaluate behavioral signals instantly to detect anomalies, trigger alerts, and support accurate attribution — all with built-in analytics capabilities.
Mobile, CTV, and streaming
Activate high-velocity signals from apps, CTV, and OTT platforms without latency spikes — even during peak concurrency windows.
Retail media and ad serving
Optimize impressions with contextual data and real-time audience matching — across on-site, off-site, and partner networks.
NoSQL databases in AdTech
| Feature/ Criteria | |
|
|
ElastiCache | |
|
|---|---|---|---|---|---|---|
| Latency Under Load | Consistent sub-ms P99 | Can spike under RTB loads | High cost in infrastructure and difficult to manage for write-heavy traffic | Great for reads, ok for real-time writes | Sub-ms possible, but not consistent | Latency spikes due to compaction |
| Write Performance | Optimized for high-frequency updates | Scales but throttles under bursty loads | Write speed depends on memory and I/O; sustaining high throughput is difficult at scale. | Extremely fast, but not durable | Good, but tuning-intensive | Suffers from compaction & write stalls |
| Scaling Efficiency | 10x more QPS per node vs others | Auto-scales but gets expensive fast | Complex tuning at scale | Costly and can block scale down | Require more nodes for same throughput | 3-5x more nodes than Aerospike |
| Operational Complexity | Minimal tuning, no compaction, self-healing | Serverless, but limited tuning control | Requires deep tuning past 5TB | Easy to spin up, limited DB capability | Deep tuning required | High ops overhead (tuning, repair, compaction) |
| Architecture | Hybrid memory (DRAM + SSD), active-active, geo-distributed | Serverless with multi-region | Cache + document store hybrid | In-memory, distributed caching with optional replication and sharding. | Shared-nothing model | Peer-to-peer, but ops-heavy |
| Cost Efficiency (TCO) | Up to 80% lower infra cost | Expensive at scale | Less efficient at high scale, infra costs rise with workload growth | Memory-heavy and expensive for persistence | More nodes = more cost | Server sprawl increases infra cost |
| AI/ML & Privacy Readiness | Real-time ML, future-proofed for privacy laws (GDPR, CCPA) | No built-in ML inference or privacy tooling | RecentAI enhancements in the platform | Not applicable | Needs external ML pipeline | No AI/ML native capabilities |
| AdTech Fit | Purpose-built for RTB, CTV, Data Platforms, Fraud detection | Works for AWS-native shops, but costly and inconsistent | Better for hybrid apps, not extreme scale | Read-only cache for ephemeral data | Good throughput, but lacks RTB reliability | Best for batch logging and write-heavy apps, not RTB |
| Best Used For | RTB, Audience Targeting, Data Platforms, CTV, Fraud Detection | Small-to-mid RTB, AWS-native stacks | Hybrid cloud apps with JSON flexibility | Caching (temporary data), not primary DB | Logging, burst writes, mid-scale infra | Large-scale writes, archival workloads |
| Native Graph Support | Yes (User Journey + Product graphs) | No | No | No | No | No |
| Multi-Model One DB | Document, KV, Graph all in one engine | KV and Document | Document, KV, FTS, Analytics in one engine | Key value, Structured Data Types mimic Document | Single-model | Single-model |
| Real-Time Personalization | Embeddings + profiles in same DB | Limited to external ML pipelines | Not native | Not applicable | Batch-oriented | No ANN or embedding support |
| Ideal for Commerce Media | Purpose-built | Costly at scale | Lack graph capabilities | Cache only | Too complex | Lacks real-time personalization |
Built for your role
Whether you're building low-latency pipelines, designing global systems, or optimizing infrastructure at scale — Aerospike is purpose-built for your priorities.
Technical capabilities
Built for speed, scale, and simplicity, Aerospike delivers the core technical capabilities modern AdTech teams need to power real-time decisions — without compromise.
Real-time streaming lookups
Deliver decision-critical data instantly across RTB platforms, exchanges, and user profiles — with sub-ms latency at scale.
Signal aggregation at scale
Hydrate your systems with contextual, viewability, identity, and behavioral data — streamed in milliseconds, not minutes.
Geo-distributed by design
Run active-active clusters across regions, clouds, or hybrid environments with zero-latency handoffs — and 99.99% uptime.
Seamless integration
Use native connectors and SDKs (Python, Java, Go), plus built-in observability (Prometheus, Grafana), to drop into your stack with zero replatforming.
Journey and purchase graphs
Model user paths, ad interactions, and product relationships in real time using built-in graph queries for smarter targeting and optimization.
Testimonials
Senior architects and engineers have learned firsthand how Aerospike's low latency, predictable performance, and operational efficiency have improved their businesses.
Aerospike is Adform’s secret weapon—the enabling data store that allows us to do real-time bidding and make money.
Aerospike is fast, predictable, reliable, and handles large volumes of data, enabling us to provide real-time reporting back to advertisers and giving us an edge over competitors.
Peter Milne
AdformSenior ArchitectWe started doing an evaluation against Cassandra, HBase. Those were the main two ones that we looked at. Postgres pretty much didn’t get consideration because it was getting too expensive. And Aerospike was definitely coming out head-and-shoulders above and with respect to two important parameters…the latency at the 95th percentile…and the throughput that it can sustain.
Sandeep Nawathe
AdobeVP EngineeringThe ability to replicate data across regions is something that Aerospike provides that very (few) other NoSQL databases do with ease. Without Aerospike, we’d be looking for a new NoSQL data store that performs as well as Aerospike does, and I haven’t seen one out there.
Henry Snow
NielsenVP, Infrastructure, Nielsen Marketing CloudWorking with Aerospike has been surprising in some ways because of how easy it is to get started using it and just how simple it is to manage and deal with failures.
Albert Autin
The Trade DeskLead Database Reliability EngineeringOur data demands are growing exponentially, and we need a real-time data platform that can handle our current requirements but ensure that we can adapt and scale for what lies ahead. The Aerospike real-time data platform takes us to the next level in terms of scale and performance and provides us with a standardized platform that ensures our customers can meet the rapid response times they demand both now and in the future.
Diarmuid Gill
Criteo CTOAdditional resources
For a deeper understanding and more insights, explore these additional resources.
- Webinar
Cracking the code: Defeat signal loss in AdTech with graph databases
Signal loss can be detrimental to advertisers who need informative, quality data — see how graph databases can help make signal loss inconsequential. - Blog
Boost Buy-Side AdTech Efficiency with Aerospike's Real-Time Solutions
Unleash the potential of your AdTech with Aerospike's low latency and high throughput solutions, ideal for real-time bidding and data-driven ad strategies. - Blog
The Future of Publisher Monetization in the AI Web
As AI reshapes content consumption, publishers need new tools to protect and monetize their work. Read about a protocol built for the machine-readable web.
Get started with Aerospike
For high-performance, scalable data management and ultra-low latency, ideal for handling massive datasets and real-time applications.