The Cypher property graph query language is an evolving language, originally designed and implemented as part of the Neo4j graph database, and it is currently used by several commercial database products and researchers. We describe Cypher 9, which is the first version of the language governed by the openCypher Implementers Group. We first introduce the language by example, and describe its uses in industry. We then provide a formal semantic definition of the core read-query features of Cypher, including its variant of the property graph data model, and its "ASCII Art" graph pattern matching mechanism for expressing subgraphs of interest to an application. We compare the features of Cypher to other property graph query languages, and describe extensions, at an advanced stage of development, which will form part of Cypher 10, turning the language into a compositional language which supports graph projections and multiple named graphs.

As graph databases become widespread, JTC1-the committee in joint charge of information technology standards for the International Organization for Standardization (ISO), and International Electrotechnical Commission (IEC)-has approved a project to create GQL, a standard property graph query language. This complements a project to extend SQL with a new part, SQL/PGQ, which specifies how to define graph views over an SQL tabular schema, and to run read-only queries against them.Both projects have been assigned to the ISO/IEC JTC1 SC32 working group for Database Languages, WG3, which continues to maintain and enhance SQL as a whole. This common responsibility helps enforce a policy that the identical core of both PGQ and GQL is a graph pattern matching sub-language, here termed GPML.The WG3 design process is also analyzed by an academic working group, part of the Linked Data Benchmark Council (LDBC), whose task is to produce a formal semantics of these graph data languages, which complements their standard specifications.

Abstract. We consider query answering using views on graph databases, i.e. databases structured as edge-labeled graphs. We mainly consider views and queries specified by Regular Path Queries (RPQ). These are queries selecting pairs of nodes in a graph database that are connected via a path whose sequence of edge labels belongs to some regular language. We say that a view V determines a query Q if for all graph databases D, the view image V(D) always contains enough information to answer Q on D. In other words, there is a well defined function from V(D) to Q(D).Our main result shows that when this function is monotone, there exists a rewriting of Q as a Datalog query over the view instance V(D). In particular the rewriting query can be evaluated in time polynomial in the size of V(D). Moreover this implies that it is decidable whether an RPQ query can be rewritten in Datalog using RPQ views.

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We consider the view determinacy problem over graph databases for queries defined as (possibly infinite) unions of path queries. These queries select pairs of nodes in a graph that are connected through a path whose length falls in a given set. A view specification is a set of such queries. We say that a view specification V determines a query Q if, for all databases D, the answers to V on D contain enough information to answer Q.Our main result states that, given a view V, there exists an explicit bound that depends on V such that we can decide the determinacy problem for all queries that ask for a path longer than this bound, and provide first-order rewritings for the queries that are determined. We call this notion asymptotic determinacy. As a corollary, we can also compute the set of almost all path queries that are determined by V. ACM Subject Classification IntroductionView determinacy is a static analysis problem on databases that consists in deciding whether a given set of initial queries, called a view, contains enough information to answer a new query, and this on all databases. Solving this problem has many applications, namely in query optimization and caching. Assume that querying the database is costly, but that answers to all previous queries are kept in cache. Then it is useful to know whether a new query can be answered using only cached information and without accessing the database. Query determinacy can also be stated as a security problem. Assume that views represent information that can be publicly accessed, but that the considered query contains private data that should not be disclosed. Then it should be ensured that the view does not determine the query. We consider this question over graph databases. Graph databases are relational databases in which all relations are binary. Equivalently, they can be seen as directed graphs with edges labeled from a finite alphabet. Such databases arise naturally in several scenarios, which include social networks, crime detection, biological data and the semantic Web. For instance, in social networks, individual data such as name or phone number are represented as nodes, whereas relationships between members of the network are edges linking the corresponding nodes and labeled by the nature of the relationship. Thus, a person X is a friend of a person Y if there is an edge going from X to Y with label friend.Information contained in a graph database does not only lie in the content of the graph but also in its topology, that is in how the different data nodes are connected to each other. Typical queries then naturally ask about topological properties of the graph, namely the © Nadime Francis; licensed under Creative Commons License CC-BY 18th International Conference on Database Theory (ICDT'15).