Extending Eventually Consistent Cloud Databases for Enforcing Numeric Invariants

Geo-replicated databases often operate under the principle of eventual consistency to offer high-availability with low latency on a simple key/value store abstraction. Recently, some have adopted commutative data types to provide seamless reconciliation for special purpose data types, such as counters. Despite this, the inability to enforce numeric invariants across all replicas still remains a key shortcoming of relying on the limited guarantees of eventual consistency storage. We present a new replicated data type, called bounded counter, which adds support for numeric invariants to eventually consistent geo-replicated databases. We describe how this can be implemented on top of existing cloud stores without modifying them, using Riak as an example. Our approach adapts ideas from escrow transactions to devise a solution that is decentralized, fault-tolerant and fast. Our evaluation shows much lower latency and better scalability than the traditional approach of using strong consistency to enforce numeric invariants, thus alleviating the tension between consistency and availability

Eventual Consistency: Origin and Support

Eventual consistency is demanded nowadays in geo-replicated services that need to be highly scalable and available. According to the CAP constraints, when network partitions may arise, a distributed service should choose between being strongly consistent or being highly available. Since scalable services should be available, a relaxed consistency (while the network is partitioned) is the preferred choice. Eventual consistency is not a common data-centric consistency model, but only a state convergence condition to be added to a relaxed consistency model. There are still several aspects of eventual consistency that have not been analysed in depth in previous works: 1. which are the oldest replication proposals providing eventual consistency, 2. which replica consistency models provide the best basis for building eventually consistent services, 3. which mechanisms should be considered for implementing an eventually consistent service, and 4. which are the best combinations of those mechanisms for achieving different concrete goals. This paper provides some notes on these important topics

Eventual Consistent Databases: State of the Art

One of the challenges of cloud programming is to achieve the right balance between the availability and consistency in a distributed database. Cloud computing environments, particularly cloud databases, are rapidly increasing in importance, acceptance and usage in major applications, which need the partition-tolerance and availability for scalability purposes, but sacrifice the consistency side (CAP theorem). In these environments, the data accessed by users is stored in a highly available storage system, thus the use of paradigms such as eventual consistency became more widespread. In this paper, we review the state-of-the-art database systems using eventual consistency from both industry and research. Based on this review, we discuss the advantages and disadvantages of eventual consistency, and identify the future research challenges on the databases using eventual consistency

Invariant preservation in geo-replicated data stores

The Internet has enabled people from all around the globe to communicate with each other in a matter of milliseconds. This possibility has a great impact in the way we work, behave and communicate, while the full extent of possibilities are yet to be known. As we become more dependent of Internet services, the more important is to ensure that these systems operate correctly, with low latency and high availability for millions of clients scattered all around the globe. To be able to provide service to a large number of clients, and low access latency for clients in different geographical locations, Internet services typically rely on georeplicated storage systems. Replication comes with costs that may affect service quality. To propagate updates between replicas, systems either choose to lose consistency in favor of better availability and latency (weak consistency), or maintain consistency, but the system might become unavailable during partitioning (strong consistency). In practice, many production systems rely on weak consistency storage systems to enhance user experience, overlooking that applications can become incorrect due to the weaker consistency assumptions. In this thesis, we study how to exploit application’s semantics to build correct applications without affecting the availability and latency of operations. We propose a new consistency model that breaks apart from traditional knowledge that applications consistency is dependent on coordinating the execution of operations across replicas. We show that it is possible to execute most operations with low latency and in an highly available way, while preserving application’s correctness. Our approach consists in specifying the fundamental properties that define the correctness of applications, i.e. the application invariants, and identify and prevent concurrent executions that potentially can make the state of the database inconsistent, i.e. that may violate some invariant. We explore different, complementary, approaches to implement this model. The Indigo approach consists in preventing conflicting operations from executing concurrently, by restricting the operations that each replica can execute at each moment to maintain application’s correctness. The IPA approach does not preclude the execution of any operation, ensuring high availability. To maintain application correctness, operations are modified to prevent invariant violations during replica reconciliation, or, if modifying operations provides an unsatisfactory semantics, it is possible to correct any invariant violations before a client can read an inconsistent state, by executing compensations. Evaluation shows that our approaches can ensure both low latency and high availability for most operations in common Internet application workloads, with small execution overhead in comparison to unmodified weak consistency systems, while enforcing application invariants, as in strong consistency systems

A New Model for Testing CRUD Operations in a NoSQL Database

NoSQL databases provide high availability and efficiency in data processing but at the expense of weaker consistency. In this paper, we propose a new approach in order to test NoSQL key/value databases in general and their CRUD operations in particular. We design a new context-aware model that takes into account the contextual requirements of clients (users) and the NoSQL database system. Accordingly, we develop a transaction model and testing criteria in order to test NoSQL databases by taking into account transactional and nontransactional CRUD operations. Results from testing criteria are used to analyse the trade-off between availability and consistency of NoSQL databases. In addition, these are used to help NoSQL database users and developers to choose between transactional and non-transactional CRUD operations.