A practitioner’s guide to building Knowledge Graphs for the enterprise.

A practice and humane introduction to graph databases and Neo4j, Graph Databases For Dummies walks you through modeling, querying, and importing graph data, all the way through to your first production system.

The first book on graph databases, now in its second edition. Provides in-depth coverage of graph modeling and querying, as well as thorough explanations of the internal workings of Neo4j.

Why don’t typical enterprise projects go as smoothly as projects you develop for the Web? Does the REST architectural style really present a viable alternative for building distributed systems and enterprise-class applications?

In this insightful book, three SOA experts provide a down-to-earth explanation of REST and demonstrate how you can develop simple and elegant distributed hypermedia systems by applying the Web’s guiding principles to common enterprise computing problems. You’ll learn techniques for implementing specific Web technologies and patterns to solve the needs of a typical company as it grows from modest beginnings to become a global enterprise.

This was one of the first books to demonstrate how to build (WS-*) Web Services with enterprise-class reliability, and performance. This book takes a no-nonsense view of architecting and constructing enterprise-class Web services and applications. The authors assess the state of the art of the Web services platform circa 2004, offering best practices and new architectural patterns for taking advantage of Web Services.

While the architectural patterns in this book generally remain worthwhile today, the protocols and standards covered are now looking somewhat out of date, especially since there is a strong groundswell towards building RESTful systems on the Web rather than tunnelling through HTTP with XML payloads.

Consensus protocols such as Raft and Paxos implement state machine replication through a single leader that enforces a totally ordered log. While this simplifies correctness, it introduces sequential bottlenecks that restrict scalability. We present RIOT, a generalized consensus protocol that eliminates centralized leadership and log replication in favor of decentralized coordination over a directed acyclic graph (DAG) of entries. RIOT guarantees that all servers maintain a logically identical DAG, preserving order where conflicts require it while allowing commutative operations to execute concurrently. RIOT is motivated by our work on distributed graph databases,which must guarantee reciprocal consistency for edges that span shards. Unlike specialized transaction protocols, RIOT makes no assumptions about concurrency control or transaction models. It provides a replicated state machine abstraction that integrates cleanly with transactional databases, treating DAG entries as transaction placeholders. Both single-phase and two-phase variants are supported, ensuring atomic agreement on entries and their ordering constraints. We integrate RIOT with Neo4j and evaluate it against Neo4j’s production Raft implementation. For common workloads, RIOT delivers up to 2.5× higher throughput and 2.3× lower tail latency while matching the strong consistency guarantees of log-based consensus. In doing so, RIOT demonstrates how consensus can be generalized to unlock scalability for transactional databases at scale.

In a system containing several distributed servers, messages of random sizes generated at different locations must be disseminated and processed in the same order by all hosts. A ring protocol is defined, where a number of folders carrying messages circulate in one direction without overtaking each other. A model involving parallel queues is analysed in the steady state and is solved approximately, allowing the computation of performance measures. A number of example systems are evaluated numerically and by simulations, leading to a heuristic for choosing the optimal number of folders.

Mammoth transactions, which involve long-running operations that access many items, are common in graph workloads. Graph analytics tasks, including pattern matching and graph algorithms, can generate large read-write operations that impact signi!cant portions of data, which makes their execution challenging under strict isolation guarantees. Consequently, we face an apparent trade-off between ensuring high isolation and achieving high performance, forcing users to choose between the two. In this work, we present TuskFlow, an experimental graph database based on Neo4j, designed to e#ciently handle mammoth transactions on graphs (the technique is applicable to other models such as relational) while maintaining existing transactional semantics. TuskFlow employs a deterministic protocol that safely reorders regular transactions around mammoths within an epoch. Our protocol supports parallel mammoth execution inspired by graph-parallel algorithms. To minimize con$icts with regular transactions, TuskFlow introduces query- and workload-aware optimizations, including graph entity tagging and partitioning. Our experiments demonstrate that, unlike traditional protocols like two-phase locking or MVCC, TuskFlow avoids blocking write transactions and improves tail latency by up to 45x.

We present a database replication architecture that guarantees ACID transaction properties as well as high throughput expected of modern database systems. Higher throughput results due to server replicas processing distinct, non-overlapping subsets of incoming transactions in parallel. Our novel approach addresses all challenges that emerge in ensuring ACID properties across all incoming transactions processed in parallel even when access pattern of transactions is not known a priori. At the core of our approach is a high-throughput, ring-based total order protocol which the database replicas use to reach consensus for resolving conflicts among transactions, ensuring serializability and accomplishing atomic commit. After presenting the architecture, protocol performance is evaluated through implementations when replication degree is two and three, tolerating at most one replica crash. While 2-fold replication requires perfect crash detection, three-fold can do with weak detectors.

In this paper, we describe No-Wait concurrency control mechanisms to address conflict resolution and then comprehensively evaluate their performance under Read-Committed and Serializability isolation levels using an in-memory database system in various configurations and contention scenarios. Key performance metrics are percentage of transaction aborts and average latency for those who do not abort. Our evaluations affirm that the No-Wait approach indeed offers a cost-effective, practical alternative to traditional conflict resolution mechanisms.