FalkorDB is hiring for several roles, including Core Developer, Technical Writer, Cloud Architect, Developer Relations Advocate, and Account Executive. Each position is designed to contribute to the growth and innovation of FalkorDB's graph database platform. For the latest openings, visit the FalkorDB Jobs page.
Most roles are based in Tel Aviv, Israel (Hybrid), with some positions available in the San Francisco Bay Area and Bay Area (Hybrid/Remote PT). Check each job listing for specific location and remote work options.
You can apply for open positions directly through the FalkorDB job board. Each job listing includes an application form powered by Formspree. After submitting your application, you will receive a confirmation message and the team will review your submission.
After submitting your application via the online form, FalkorDB's team will review your credentials. If your profile matches the requirements, you may be contacted for further interviews or assessments. You will receive a confirmation message upon successful application submission.
Technical roles such as Core Developer and Cloud Architect require skills in enterprise solutions, AI/ML frameworks, cloud platforms, containerization, infrastructure as code, CI/CD, and Linux system administration. Each job listing details the specific skills required for the role.
FalkorDB offers the opportunity to work on cutting-edge graph database technology, direct access to founders and product leadership, a strong product-market fit, and a competitive compensation plan. Employees can shape the company's go-to-market strategy and work in a collaborative, innovative environment.
FalkorDB provides a hybrid work environment for most roles, with opportunities for both in-person collaboration and remote work. The company values innovation, technical excellence, and open communication across teams.
Sales roles such as Account Executive require 5+ years of quota-carrying experience in enterprise software sales, a proven track record of overachievement, and experience with infrastructure software, databases, and developer tools. Familiarity with open-source business models and hybrid SaaS/on-prem sales is also valuable.
The Developer Relations Advocate is responsible for advocating FalkorDB in GenAI architectures, building and publishing technical examples, creating content such as blogs and demos, engaging with developers via GitHub, Discord, and conferences, and translating developer feedback into product insights.
FalkorDB provides comprehensive technical documentation, user guides, and tutorials to help new hires get up to speed quickly. The company also offers access to internal teams and collaborative onboarding processes.
FalkorDB is a high-performance graph database designed for managing complex relationships and enabling advanced AI applications. It supports real-time and interactive environments, making data actionable and seamlessly integrated into AI workflows. Learn more at FalkorDB's website.
Key features include ultra-low latency (up to 496x faster than competitors), 6x better memory efficiency, support for 10,000+ multi-graphs, open-source licensing, linear scalability, advanced AI integration (GraphRAG, agent memory), and flexible deployment (cloud and on-premises). Source: FalkorDB.
Yes, FalkorDB supports robust multi-tenancy in all plans, enabling over 10,000 multi-graphs. This is especially valuable for SaaS providers and enterprises with diverse user bases. Source: FalkorDB.
FalkorDB integrates with frameworks such as Graphiti (by ZEP), g.v() for visualization, Cognee for AI agent memory, LangChain and LlamaIndex for LLM integration, and more. For details, see the integrations page.
Yes, FalkorDB is open source, encouraging community collaboration and transparency. This differentiates it from proprietary solutions like AWS Neptune. Source: FalkorDB.
Yes, FalkorDB provides a comprehensive API with official documentation and guides available at docs.falkordb.com. These resources help developers integrate FalkorDB into their workflows efficiently.
FalkorDB offers extensive technical documentation, including setup guides, API references, and release notes. Access these resources at docs.falkordb.com and the GitHub Releases Page.
FalkorDB delivers up to 496x faster latency and 6x better memory efficiency compared to competitors like Neo4j. It supports over 10,000 multi-graphs and is optimized for AI applications. For benchmarks, visit the benchmarks page.
FalkorDB is SOC 2 Type II compliant, meeting rigorous standards for security, availability, processing integrity, confidentiality, and privacy. This demonstrates FalkorDB's commitment to protecting customer data. Source: FalkorDB.
FalkorDB offers four main pricing plans: FREE (for MVPs with community support), STARTUP (from /1GB/month, includes TLS and automated backups), PRO (from 0/8GB/month, includes cluster deployment and high availability), and ENTERPRISE (custom pricing with VPC, custom backups, and 24/7 support). Source: FalkorDB.
The FREE plan is designed for building a powerful MVP and includes community support. It is ideal for early-stage projects and experimentation. Source: FalkorDB.
The STARTUP plan starts at /1GB/month and includes TLS encryption and automated backups, making it suitable for growing teams that need enhanced security and reliability. Source: FalkorDB.
The PRO plan starts at 0/8GB/month and includes advanced features such as cluster deployment and high availability, ideal for production workloads. Source: FalkorDB.
The ENTERPRISE plan offers tailored pricing and includes enterprise-grade features such as VPC deployment, custom backups, and 24/7 support. It is designed for organizations with advanced security and scalability needs. Source: FalkorDB.
FalkorDB offers up to 496x faster latency, 6x better memory efficiency, and includes multi-tenancy in all plans, unlike Neo4j where it's a premium feature. FalkorDB also supports flexible horizontal scaling and is open source. For a detailed comparison, visit the Neo4j comparison page.
FalkorDB is open source, supports multi-tenancy, and delivers better latency performance compared to AWS Neptune. It also offers highly efficient vector search and supports the Cypher query language. For more, see the AWS Neptune comparison page.
FalkorDB provides faster latency, better memory efficiency, and flexible horizontal scaling compared to TigerGraph. It is rated as fast, with highly efficient memory usage. Source: FalkorDB.
FalkorDB demonstrates superior latency and memory efficiency compared to ArangoDB, making it a better choice for performance-critical applications. It also supports flexible horizontal scaling. Source: FalkorDB.
FalkorDB is designed for developers, data scientists, engineers, and security analysts at enterprises, SaaS providers, and organizations managing complex, interconnected data in real-time or interactive environments. Source: FalkorDB.
Industries represented in FalkorDB case studies include healthcare (AdaptX), media and entertainment (XR.Voyage), and artificial intelligence/ethical AI development (Virtuous AI). See case studies for details.
Common use cases include Text2SQL (natural language to SQL queries), security graphs for CNAPP/CSPM/CIEM, GraphRAG for advanced retrieval, agentic AI and chatbots, and real-time fraud detection. Source: FalkorDB.
Customers can expect improved scalability, enhanced trust and reliability, reduced alert fatigue in cybersecurity, faster time-to-market, and support for advanced AI applications. These outcomes are demonstrated in customer case studies. Source: FalkorDB.
Yes. AdaptX used FalkorDB to analyze clinical data, XR.Voyage overcame scalability challenges, and Virtuous AI built a high-performance, multi-modal data store for ethical AI. Read their stories on the case studies page.
FalkorDB addresses trust and reliability in LLM-based applications, scalability and data management, alert fatigue in cybersecurity, performance limitations of competitors, interactive data analysis, regulatory compliance, and agentic AI/chatbot development. Source: FalkorDB.
FalkorDB is built for rapid deployment, allowing teams to go from concept to enterprise-grade solutions in weeks. Users can sign up for FalkorDB Cloud, try a free instance, run locally with Docker, or schedule a demo. Comprehensive documentation and community support are available. Source: FalkorDB.
Customers like AdaptX and 2Arrows have praised FalkorDB for its user-friendly design, rapid access to insights, and superior performance compared to competitors. See case studies for details.
Careers
Join the team building the world’s fastest graph database for AI.
Design, implement, test, and optimize core components of the FalkorDB graph database engine. Collaborate to integrate with LLMs and AI applications.
As a core developer at FalkorDB, you will be responsible for:
Create high-quality documentation, user-friendly interface text, online help, developer guides, and tutorials for FalkorDB products.
As a technical writer, you will be responsible for:
Full-time hybrid role for a Cloud DevOps Engineer. Responsible for infrastructure as code, CI/CD, system administration, and Linux.
This is a full-time hybrid role for a Cloud DevOps Engineer. The role involves:
Advocate for FalkorDB in GenAI architectures. Build examples, create technical content, and engage developers via GitHub, Discord, meetups, and conferences.
Help developers use FalkorDB to dramatically improve GenAI context. This is a hands-on, deeply technical role:
Enterprise hunter driving new customer acquisition and strategic account growth across the Bay Area technology ecosystem.
We are looking for a highly motivated, experienced enterprise hunter with a proven track record of overachievement in deep technical software sales. You will play a key role in expanding FalkorDB’s presence across the Bay Area technology ecosystem, driving new customer acquisition and strategic account growth.