Event Store vs Google Cloud Spanner

Overview

Event Store

Stacks69

Followers82

Votes1

Google Cloud Spanner

Stacks57

Followers117

Votes3

GitHub Stars2.0K

Forks1.1K

Event Store vs Google Cloud Spanner: What are the differences?

Introduction: Event Store and Google Cloud Spanner are two different data storage systems that are used for different purposes. The key differences between Event Store and Google Cloud Spanner are as follows:

Data Model: Event Store is a log-based database that stores events, while Google Cloud Spanner is a globally distributed relational database. Event Store captures and stores every change as an event, allowing for event sourcing and event-driven architectures. On the other hand, Google Cloud Spanner provides ACID-compliant transactions on a distributed relational database model, allowing for structured data storage and querying.
Scalability: Event Store is designed for horizontal scalability and can handle large volumes of events efficiently. It supports a scalable and distributed architecture for event-driven applications. Google Cloud Spanner, on the other hand, is a highly scalable relational database system that can automatically partition data across multiple nodes. It is designed to handle massive workloads and provide consistent performance across regions.
Consistency and Availability: Event Store provides eventual consistency by default, as events are stored and processed asynchronously. It allows for eventual consistency and event replay for building event-driven systems. Google Cloud Spanner, on the other hand, provides strong consistency guarantees within a region and external consistency across regions. It ensures high availability by replication and automatic failover.
Multi-region Support: Google Cloud Spanner has built-in multi-region support, allowing for global deployments and data replication across regions. It provides strong consistency guarantees even in the face of network partitions or infrastructure failures. Event Store does not have built-in multi-region support and is primarily designed for local or regional deployments.
Querying Capabilities: Event Store provides a rich set of query options that can be used to query events based on different criteria. These include simple linear queries, temporal queries, and projections. Google Cloud Spanner, being a relational database, offers SQL-like querying capabilities along with support for joins, indexes, and transactions.
Integration: Event Store is often used in event-driven architectures and can be integrated with other components of event-driven systems such as message queues, event routers, or stream processing frameworks. Google Cloud Spanner integrates well with other Google Cloud services and can be easily connected with applications running on Google Cloud Platform.

In summary, Event Store is a log-based database for storing events in an event-driven architecture, while Google Cloud Spanner is a globally distributed relational database. Event Store is designed for scalability and eventual consistency, with a focus on event sourcing. Google Cloud Spanner, on the other hand, offers strong consistency, multi-region support, and SQL-like querying capabilities for structured data.

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Detailed Comparison

Event Store	Google Cloud Spanner
It stores your data as a series of immutable events over time, making it easy to build event-sourced applications. It can run as a cluster of nodes containing the same data, which remains available for writes provided at least half the nodes are alive and connected.	It is a globally distributed database service that gives developers a production-ready storage solution. It provides key features such as global transactions, strongly consistent reads, and automatic multi-site replication and failover.
Guaranteed writes; High availability; Projections; Multiple client interfaces; Optimistic concurrency checks; Subscribe to streams with competing consumers; Great performance that scales; Multiple hosting options; Commercial support plans; Immutable data store; Atom subscriptions	Global transactions; Strongly consistent reads; Automatic multi-site replication; Failover.
Statistics
GitHub Stars -	GitHub Stars 2.0K
GitHub Forks -	GitHub Forks 1.1K
Stacks 69	Stacks 57
Followers 82	Followers 117
Votes 1	Votes 3
Pros & Cons
Pros 1 Trail Log	Pros 1 Scalable 1 Horizontal scaling 1 Strongly consistent
Integrations
.NET SQLite MySQL	MySQL PostgreSQL MongoDB SQLite

What are some alternatives to Event Store, Google Cloud Spanner?

MongoDB

MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.

MySQL

The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.

PostgreSQL

PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

MariaDB

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

ArangoDB

A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.

Related Comparisons

Event Store vs Google Cloud Spanner: What are the differences?

Data Model: Event Store is a log-based database that stores events, while Google Cloud Spanner is a globally distributed relational database. Event Store captures and stores every change as an event, allowing for event sourcing and event-driven architectures. On the other hand, Google Cloud Spanner provides ACID-compliant transactions on a distributed relational database model, allowing for structured data storage and querying.
Scalability: Event Store is designed for horizontal scalability and can handle large volumes of events efficiently. It supports a scalable and distributed architecture for event-driven applications. Google Cloud Spanner, on the other hand, is a highly scalable relational database system that can automatically partition data across multiple nodes. It is designed to handle massive workloads and provide consistent performance across regions.
Consistency and Availability: Event Store provides eventual consistency by default, as events are stored and processed asynchronously. It allows for eventual consistency and event replay for building event-driven systems. Google Cloud Spanner, on the other hand, provides strong consistency guarantees within a region and external consistency across regions. It ensures high availability by replication and automatic failover.
Multi-region Support: Google Cloud Spanner has built-in multi-region support, allowing for global deployments and data replication across regions. It provides strong consistency guarantees even in the face of network partitions or infrastructure failures. Event Store does not have built-in multi-region support and is primarily designed for local or regional deployments.
Querying Capabilities: Event Store provides a rich set of query options that can be used to query events based on different criteria. These include simple linear queries, temporal queries, and projections. Google Cloud Spanner, being a relational database, offers SQL-like querying capabilities along with support for joins, indexes, and transactions.
Integration: Event Store is often used in event-driven architectures and can be integrated with other components of event-driven systems such as message queues, event routers, or stream processing frameworks. Google Cloud Spanner integrates well with other Google Cloud services and can be easily connected with applications running on Google Cloud Platform.

Event Store vs Google Cloud Spanner

Overview