— IT Press Tour March 16, 2022 

2 Who you met with @ SingleStore Suresh Sathyamurphy CMO @sureshcs /in/sureshcs Domenic Ravita VP of Product Marketing @DomenicRavita /in/domenic 

— 3 About SingleStore 

4 Our mission is to bring modern data together 

5 BUILDERS WE ARE 350+ 

6 Build It Like an Owner Unite in Passion, Purpose & Possibility Learn, Extend, Grow Insist on Having Impact Do Right by Our Customers & Each Other 

Customers Love SingleStore... 

8 — Middle East: Israel Egypt Saudia Arabia UAE Oman Kuwait APAC: India Singapore Australia Japan South Korea Indonesia Malaysia Vietnam Thailand LATAM: Mexico Central America Brazil Colombia Ecuador Europe: Turkey Italy VAR Coverage Office Location *Quota Carrying Resource in Country Direct Coverage North America: U.S.* Canada Europe: U.K.* France* Germany* Switzerland Austria The Netherlands* Belgium Denmark Sweden Norway Finland Spain Portugal Italy Customers in 26 Countries GEOGRAPHICAL PRESENCE — 

9 — Global Fortune 500 Leaders Across 10 Industries, 26 Countries 354 Employees 10+ Locations Worldwide Customers $266M in Funding Facts & Figures SingleStore 184% YoY Cloud Revenue Growth 136% Net Dollar Retention Rate 40% Revenue from Fortune 100 

— 10 Our Story 

One Database. Limitless Applications. SingleStore is the cloud-native database built with speed and scale to power data-intensive applications. 

12 1st Era 1999-2010 Retrofitting On-Premises, General Purpose SQL DBs 2nd Era 2010-2017 3rd Era 2017-Now Giving up on SQL to achieve speed and scale Adoption of special purpose NoSQL datastores Adoption of primitive, cheap object storage Cloud Data Evolution Real-time Multi-cloud Hybrid Multi-model Relational 

13 — CONFIDENTIAL SingleStore RISE OF GENERATION 3 DATABASE Cloud agnostic deployments Frictionless & Ultra-Fast Distributed SQL Multi-Model Hybrid & Multi-Cloud Cloud DBaas Hybrid Self-Hosted Cloud Kubernetes On-Premises Real-Time / Modern Apps 

14 — Trends driving database market disruption THE DATABASE EVOLUTION 14 ● The Internet is getting faster fueling hyper growth in the adoption of modern applications for streaming, gaming, IoT and other interactive real-time applications* ● Modern applications are also driving the need for convergence of streaming data, transactional, and analytical processing on multi-model modern data** ● Applications are being re-platformed** ● The world is going hybrid, and multi-cloud** * Fortune Business Insights, Verizon: How 5G Changes the World ** Gartner, Forrester [1] [2], RedMonk 

15 — CONFIDENTIAL 3 Tenets We Are Betting Our Future On THE DATABASE EVOLUTION 15 Companies will consolidate their database technologies The future will be hybrid, multi-cloud, frictionless and ultra-fast Distributed SQL is here to stay 1 2 3 Convergence of OLAP, OLTP will power modern apps We will be among the top 3 

— 16 The Product 

One Database. Limitless Applications. SingleStore is the cloud-native database built with speed and scale to power data-intensive applications. 

18 — Supercharging SaaS Applications Customer Facing or Internal Applications Powering Businesses Business Experience Millisecond Latencies for Operational Workloads Customer Experience Immersive Customer-Facing Applications 

19 — SaaS Everywhere Customer Facing or Internal Applications Powering Businesses Business Experience Customer Experience Tech Retail Finance Media Gaming 5 of 10 Top US Banks 

20 — 20 Requirements for the Data Tier of Modern SaaS Apps Operational (real-time UPDATE / DELETE / TRANSACTION) Fast analytics (leverage RAM + CPU parallelism) Highly scalable (Sharding) HA (Replication) SQL for BI access Start free, Grow to Global Scale 

21 — ● Performance ○ Process more than 1 trillion rows per second ○ Parallel streaming data ingestion of TB/sec ○ Low-latency, single-digit millisecond responses ○ Scale client concurrency from 1 to 1000s ● Price ○ At least 10-100x the performance at ⅓ the cost over legacy databases ○ Return on investment of 298% (Forrester TEI) ● Flexibility ○ Familiar SQL and MySQL wire-protocol compatibility ○ Multi-Model - Any data type ○ Hybrid deployment, SaaS, containers, bare metal SingleStore DB THE PRODUCT 

Columnstore + Rowstore 

SingleStore 

24 The Recipe for a Single Store Database 

25 — SingleStore’s Unique Advantages PRODUCT PERSPECTIVE Scalable, Relational SQL Distributed-native, bottomless, cloud-native, ACID, ANSI SQL Unified Data SingleStore, document, key-value, time-series, geospatial, streaming Optimized for Real-time Parallel ingestion, vectorization, lock-free, MVCC, SIMD, NVMe compressed storage, efficient distributed joins 

26 — Run Anywhere Hybrid, Multi-Cloud, SaaS, On-Premises, Kubernetes Operator Pure Speed Fast Transactions, Analytics, Vectorization, Query Compilation Compatibility ANSI SQL, MySQL & MariaDB Ecosystem Multi-Model Relational foundation with first-class support for Document, Key-Value, Geospatial, Time-Series, Full-Text Search Fast Ingestion Pipelines - Load data w/ updates Universal Storage Patented single table type for transactions and analytics. The only database, Translytical or otherwise, with a single table type for both Unlimited Storage Separation of Storage & Compute in an Operational - Analytic database Limitless Point-in-Time Recovery Key Capabilities 

27 SingleStore DB — Deployment Options Self-Managed* Customer Hardware Run on-prem or on your own hardware instances Cloud Database-as-a-Service Run in your public cloud of choice *Not all features and capabilities are available for self-managed deployments 

28 SingleStore DB — Standard SingleStoreDB Core Database Functionality Cloud Standard Support 99.9% SLA Self-Managed Standard Support Premium Standard + Features for mission critical workloads Cloud Silver Support 99.99% SLA Self-Managed Standard Support Dedicated Premium + Isolated account for regulated industries Cloud Silver Support 99.99% SLA Product Editions ✔ ✔ ✔ ✔ ✔ SingleStore Pricing 

SingleStore Product Architecture 

30 — 16 Million upserts/second Improving timeliness and accuracy of of 100 TBs of billing date across many data products 2 Billion rows/hour 50% Reduction in infrastructure 12,000x query performance 60% Reduction in monthly cloud bill 1 Million API calls/minute Improved Financial Data Distribution by 15x 90% faster queries 35% reduction in monthly costs and up to Serving 12M+ 401(k) participants S2 🔥 Stats BY THE NUMBERS 

31 — Key Innovations ● Query Optimization for Real-time Analytics ● SingleStore Pipelines ● Patented Universal Storage ○ Real-time analytics and transactions in single table type ● Bottomless, 3-tiered Storage ○ Operational Database with Separation of Storage & Compute ● Skip-list Indexing ● Universal Language & AI Support in the Database via WASM ● SingleStore Patents More info in our Research Papers: https://www.singlestore.com/resources/?category=researchpaper and in our blog: https://www.singlestore.com/blog and in our Developers Hub: https://www.singlestore.com/developers and on our Customers page: https://www.singlestore.com/customers 

AWS Database Migration Service 

33 OLAP OLTP DATABASE FOR DATA-INTENSIVE APPLICATIONS — SingleStore Positioning 33 

34 — Links to further details ADDITIONAL RESOURCES ● Trillion Rows Demo ● How to Load 100 Billion Rows in 10 Minutes ● TPC-C, TPC-H & TPC-DS Benchmarks ● “SingleStore’s Columnstore Blows All of the Free Open Source Solutions Out of the Water” ● How SingleStore Works ○ A Recipe for a Single Store Database ● Bottomless (unlimited) Storage https://www.youtube.com/singlestore on ● Patented Universal Storage ● Beyond B-tree Indexes: Lock-free Skip-list Indexes ● HTAP (Hybrid Transactional Analytical Processing) ● Akamai’s use of SingleStore ● Frequently Asked Questions 

— 35 CONFIDENTIAL The Problem We Solve 

36 Businesses are becoming data-intensive Applications are struggling to keep up Data volume and complexity are rising Delivering the best customer experiences require real-time analytics Data-hungry AI and ML models are being applied to predict outcomes and recommend products Sluggish event-to-insight response unable to meet SLAs Rising costs and complexity Growing user demands drive increased concurrency challenges 

37 CONFIDENTIAL We Now Live in the World of Data-Intensive Applications #DataIntensity 

38 What are Data-Intensive Applications? Applications that need a combination of some or all of these five attributes Data Size Speed of Ingestion Latency Requirements Complexity Concurrency Hundreds of Terabytes or Petabytes of data Thousands to Millions of rows/second Sub-second to millisecond latencies High number of joins in the queries Tens to hundreds of users accessing the application simultaneously BUT FIRST… 

39 — Existing database technologies struggle to cost-effectively solve these data challenges at scale: ● Data Freshness ● Data Diversity ● Data Size ● Data Volume ● Data Latency ● Data Changes ● Data Concurrency Many databases today are advising to choose a database-per-workload. The result is a complex, expensive data systems which still does not solve data intensity. Data Intensity How is the industry solving this challenge of data intensity? = 

40 — A quick assessment available from the SingleStore website to determine how data intensive an environment is based on 5 unique variables: Data Size, Query Latency, Query Complexity, Data Ingest Speed, and Concurrency Data Intensity Assessment Tool (in development) MEASURING DATA INTENSITY Who is it for? Sr Devs/ Engineers Application Architects Database Architects & DBAs Data Engineers How does it work? Developers answer a series of questions about these 5 characteristics of their workload and responses are scored in a document they can share Why are we building it? To help educate developers about data intensity and help them identify their data-intensive workloads and applications 

41 — Application Operational 3rd Party Batch Batch Ingest Cache Search IoT Click Stream Data Analytics AI / ML Solving Data Intensity (The Hard, Expensive Way) MODERN APPLICATIONS’ DATA CHALLENGE 

42 — Application AI / ML Operational 3rd Party Batch IoT The SingleStore Solution 

43 Crush Complexity with SingleStore — Why Enterprises Choose Us 1. To capitalize better on business imperatives 2. To gain data advantages faster 3. To achieve huge price-performance advantages 4. To reduce technical debt Customer Evidence Investment Bank Tier 1 U.S. Retail Bank 

44 CONFIDENTIAL Scalable, Relational SQL Real-time Performance Analytical Queries on Fast-Changing Data Transactional Queries Multi-Cloud Hybrid AI/ML integrations* Multi-Model Cost Competitive Comparisons *Strategic partnerships with Data Science & Machine Learning Gartner MQ Leaders, SAS and IBM 

45 — These industry benchmarks, TPC-C* and TPC-H**, show 1. Only SingleStore performs transactions and analytics in a single cloud database. 2. Only SingleStore has price-performance parity across both against industry-leading special-purpose databases for transactions (AWS Aurora MySQL) and for analytics (Snowflake and AWS Redshift) Evidence - Industry Standard Benchmark 45 SingleStore Snowflake AWS Redshift AWS Aurora MySQL *TCP-C is online transaction processing (OLTP) Benchmark ** TCP-H is Analytical processing (OLAP) / Decision Support Benchmark 

— 46 Customer Highlights 

47 — SingleStore is already part of millions of lives ● When an Uber car arrives quickly ● When your bank detects a fraudulent expense on your credit card ● When an anesthetist arrives at the right time, with the right medication, for a surgery ● When a minor is saved from a trafficking ring ● When the quality of a video stream adapts to your connection speed ● When a health agency reacts to an ongoing COVID-19 breakout in a neighborhood ● When you receive a flash discount while playing your favorite mobile game ● When a problem with your Internet connection is solved even before you complain ● When an exec decision is made at one company that makes the computers and devices you use ● When someone finds the home of their dreams 

Real-time fraud analytics for Credit card swipes in less than 50ms. Real-time geospatial insights with massive concurrency to manage 24/7 operations 300K Events per second 13x data growth moving from batch to near-real time visibility and analytics 3500+ Users 10M Upserts per second TIER-1 US Bank 50ms Real-time Fraud Detection Streaming analytics to drive proactive care and real-time recommendations 200M Rows of data are continuously analyzed Identifying trafficked children through real-time analysis & image recognition Customer Examples 

Industry Use Case Customer Examples Financial Services Media, Entertainment & Communications Cybersecurity & SaaS Energy & IoT ● Portfolio Management & Analytics ● Fraud Detection ● Algorithmic Trading, Crypto Exchange ● Dashboards & APIs ● Novus (1) (2), dailyVest ● Tier 1 U.S. Bank, Areeba ● Proof Trading, Bitwyre ● GE, IEX Cloud ● Improved CX for Internet Services ● Supply Chain Visibility ● ML Pipelines & Platforms ● Cybersecurity ● Uber, Wag!,Teespring, JLS, Katoni.dk, GoGuardian ● Dell EMC, BlueShift, The Fruit Company ● Thorn, Nyris, Epigen, Monday.com, Diwo ● Nucleus Security, Palo Alto Networks, Armis ● Ad Optimization & Ad Serving ● Streaming Media Quality Analytics ● Game Telemetry Processing ● Network Telemetry & Analytics ● Marketing Technology ● Pandora, TapJoy ● Comcast, Hulu, Disney, SSIMWave, Promethean TV ● GameLoft (1) (2), Playtika, Caffeine.TV, StreamHatchet ● Akamai, Telgoo5/VCare ● Impact, Fathom Analytics, Captain Metrics ● IoT & Smart Meter Analytics ● Predictive Maintenance ● Geospatial Tracking & Calculations ● Dashboards & APIs ● Infiswift, Insite360 ● EOG Resources ● True Digital ● Insite360 Data-Intensive Use Cases by Vertical 

50 SingleStore in Financial Services ● Portfolio Analytics ● Real-Time Fraud Analytics ● Algorithmic Trading ● Wealth Management ● Dynamic offers and campaigns ● Data Marketplaces ● Payment Hubs ● Fastboards Powering cutting-edge Industry Use Cases Banking FinTech Capital Markets Payments & Lending Across Key Segments Serving Industry Leaders & Disruptors 50ms Real-time fraud detection 40K Users for portfolio dashboards with millisecond responses 

51 SingleStore in Financial Services ● Real-Time Ad Targeting & Personalization ● Streaming Media Quality Analytics ● Predictive Content Recommendations ● Ad Analytics & Optimization ● Content Personalization ● Gaming Telemetry Processing ● Omnichannel Media Activation, Testing and Measurement Powering Cutting-Edge Industry Use Cases Media Streaming Gaming MediaTech Across Key Segments Serving Industry Leaders & Disruptors 98% Improvement in latencies for analytics 300K Events/second ingested with simultaneous queries for fast insights SingleStore for Media & Entertainment | Delivering Real-Time Insights with SingleStore 5 of the Top 10 Media Companies Powered by SingleStore 

52 — Devs ❤ SingleStore DEVELOPER COMMUNITY 

53 — Case Study FATHOM ANALYTICS 800TB Of Data in the Cluster 1Mn Queries per minute from API calls 

CONFIDENTIAL IEX Cloud: Overview Fast Applications: Modernization Industry: Financial Services Company Overview: IEX Cloud is a next gen, easy-to-use financial data platform that makes a wide range of market data including - stock prices, fundamentals, forex data, crypto data and more - accessible to everyone in one place. Data Intensive Application: ● Data Size ● Speed of Ingestion ● Latency Requirements ● Complexity ● Concurrency Serving more than 100,000 users, IEX Cloud needed a fast and scalable data platform, under the covers, to be able to run real-time analytics on more than 400,000 events per second. 54 

Fast ingest with simultaneous interactive analytics for immediate event-to-insight for social tracking to prevent new outbreaks of COVID-19 cases throughout the country. 1 Million Movements/Second 55 — Case Study TELECOM “We chose SingleStore because no other product that we could find was able to do geolocation calculations for our scenario as fast as they could.” Jean-Francois Gebhart, COO of IoT, True Digital 

Tracepulse SINGLESTORE 56 CONFIDENTIAL 17 days 500k events/s > 30 million “Delivering solutions which address this crisis are the top priority of telecom companies right now.” CTO of Leading System Integrator in APJ 

57 Challenges Difficulty in Tracking COVID-19 Cases: Carriers can be asymptomatic for as much as two weeks while unknowingly spreading the virus. Poor User Experience: Government officials require a low-latency application in order to immediately and proactively determine location hubs of increasing population density. Technical Requirements Modern Performance: Must support event stream processing on anonymous location events for over 30 million mobile subscribers. Native Geospatial: The visualization needs to be updated in real time while supporting geoanalytic queries. Scalable: The solution must support a moving time window of undetermined duration while also handling historical data for further analysis. SingleStore Results Established a functional version of the Tracepulse system in less than 2 weeks. Enabled the visualization to provide a real-time view that is updated every 2 minutes. Processing +500K anonymous location events every second for over 30 million mobile phones. The Government authorities can now deliver a proactive approach to combating the virus. How a Telco is Helping to Flatten the Curve with SingleStore 

58 Architecture Diagram 

59 — Case Study FATHOM ANALYTICS 12,000x Improvement in Performance 60% Reduction in TCO 

60 — Case Study "We are now all-in on SingleStore managed service, which has allowed us to drop Redis, DynamoDB & MySQL, saving us an absolute fortune in monthly costs, while dramatically improving the performance" Jack Ellis Co-Founder Fathom Analytics FATHOM ANALYTICS 

61 Challenges Poor User Experience: Bad performance for interactive queries, requests getting timed out Escalating TCO: Cost-prohibitive deployment with RDS along with multiple other engines needed Poor Scalability: User concurrency limited by AWS RDS connection limits Requirements Performance at Scale: ultra-fast, high-performance queries with support for massive concurrency Costs: Control the costs to keep it under $5,000 per month Fully Managed: Needed a fully managed database-as-a-service with Enterprise adoption Building the World’s Fastest Website Analytics Platform SingleStore Results 1000x improvement in performance and speed compared to AWS RDS “Ridiculously Fast!” user experience Collapsed three different data engines (AWS RDS, Redis and DynamoDB) into one unified modern database Over 60% (+) reduction in TCO enabling them to avoid raising prices for customers, while driving growth 

SingleStore enables daily billing to increase revenue 16 million Upserts Per Second 62 — Case Study AKAMAI 

Of datasets queried 1 Trillion Rows 63 — Case Study AKAMAI 

64 Challenges Degrading Performance: Existing Oracle Exadata platform unable to scale for weekly and daily billing cycle Rising Costs: Existing database costs rising in the face of performance degradations Requirements Operational: Platform must support standard SQL and be highly available Modern Performance: Scalable ingest up to 10M events per second with low latency big data analytics for new billing demand SingleStore Results Enabled weekly (and soon daily) billing and increased revenue in 10s of millions Reduced data management costs by 5x over Exadata 100x faster performance over Exadata with 10M upserts/sec compared to 70k/sec on Exadata Growing Revenue with Real-Time Billing 

65 — Case Study With SingleStore, Hulu is able to drive real-time analytics on video stream playback Quality of Service monitoring every second while providing deeper analytics capabilities inherit in a SQL based platform. All while simplifying the architecture and reducing risk. DISNEY STREAMING | HULU 

66 — Case Study HULU 2Bn Rows/Hour Processed 50% Reduction in Infrastructure 

CONFIDENTIAL Hulu: Overview Database Sprawl: Build Industry: Media & Communications Company Overview: Hulu is a video streaming service serving over 42 million subscribers with 70,000+ television episodes and all 75+ live streaming channels. Data Intensive Application: ● Data Size ● Speed of Ingestion ● Latency Requirements ● Complexity ● Concurrency Hulu needs to track and analyze the behavior and experiences of their 42.8 million users in real-time to make in-the-moment service updates and content recommendations. This is crucial to keeping their customers happy and avoiding unnecessary churn due to excessive buffering or bad content recommendations. 67 

— 68 CONFIDENTIAL Market Recognition 

69 CONFIDENTIAL Financial Times America’s Fastest Growing Companies 2021 Rank #188 Fast Company’s World Changing Ideas Awards Category: AI & Data TrustRadius Top Rated Awards Database-as-a-Service (DBaaS) and Relational Databases. Dresner Advisory Services 2021 Industry Excellence Award Category: Industry Excellence Award and Best in Class Inc. 5000 Rank #2,624 SFBT Fastest-Growing Private Companies in the Bay Area Rank #35 Deloitte Fast 500 Rank #126 Ventana Research Digital Leadership Awards Finalist Award Wins — SingleStore won Most Innovative Use of Data in the cloud category for the Cloud Awards. 

70 CONFIDENTIAL Press Highlights & Announcements — Real-time Database Platform SingleStore Raises $80M More, Now at $940M Valuation SingleStore Helps Uber and Hulu Use Operational Data. Check out the 36-slide Pitch Deck it Used to Raise $80 Million from Insight Partners SingleStore Revamps Database Architecture to Drive Transactional Analytics Utilizing the Third Era of Databases in the Digital Services Economy Data Intensity Could be the New KPI SingleStore Makes Raleigh a Key to its Worldwide Expansion 

71 — Dave Vellante & David Foyer, SiliconAngle: “Chasing Snowflakes in Database Boomtown” Josh Blackburn, IEX Cloud “We replaced 32 data warehouses with SingleStore” Diwakar Goel, Chief Data Officer for GE ARMIS, IoT Security Company “Over 10,000 CDOs hired over the last 10 years, with a primary mandate to address the challenge of simplifying the data estate” “SingleStore enables us to do monitoring and analysis in the same system that houses historical data, and this creates enormous efficiencies for us. We have been able to consolidate multiple databases, run platform faster, and speed the onboarding process with new data sets. “ “Customers want to lower license costs, avoid database sprawl, run anywhere and manage new data types. “ “AWS “best-fit engineering” approach to databases will still have to wrestle with issues of data integration. AWS support for a world in which most organizations will have data on multiple clouds lags behind that of other hyperscale providers and most independent service providers. “ “We are replacing 400 postgres databases and 400 Elastic databases with 26 unit of SingleStore.” Gartner Magic Quadrant for Cloud DBMS - Cautions for AWS “[SAS is a] fantastic TAM opportunity for SingleStore. This is a step function above what you've been able to do so far...This should be an embarrassment of riches for you guys. Gartner analyst, Merv Adrian - Private briefing, October 2021 Validation 

— 72 CONFIDENTIAL Partner Ecosystem 

73 — CLOUD HARDWARE APPLICATIONS Hyperscalers GROWTH 

74 ●The SAS Viya platform will be powered by SingleStore ●Joint GTM at 17,000 SAS customers at 82,000 sites + SAS STRATEGIC PARTNERSHIPS — 

75 + IBM STRATEGIC PARTNERSHIPS — ●IBM is now an investor in SingleStore ●SingleStore available on IBM Cloud Data Pak ●Jointly delivers data fabric architecture to customers ●Strategic commercial partnership between the companies 

76 Embedded/ Bundled Partnerships International VAR Partnerships SI Partnerships Technology Partnerships Key Partner Ecosystem GROWTH — 

— 77 CONFIDENTIAL More info on SingleStore’s Universal Storage Unified Multi-Tier Storage: RAM, PMEM, SSD, Cloud Object Storage 

78 — CONFIDENTIAL Universal Storage Resources to learn more: ● Universal Storage video ● The development journey of Universal Storage ○ Episode 1 ○ Episode 2 ○ Episode 3 ○ Episode 4 

— Thank You