Seit über 30 Jahren basiert die Datenverwaltung in Unternehmen auf relationalen Datenbanken.
Doch die modernen Verfahren für die Entwicklung und den Betrieb von Anwendungen in Kombination mit der rasant steigenden Zahl neuer Datenquellen und den immer umfangreicheren Workloads der Anwender übersteigen zunehmend die Möglichkeiten relationaler Datenbanken. Die dadurch entstehenden Einschränkungen im Hinblick auf die Flexibilität und Skalierbarkeit sowie die steigenden finanziellen Belastungen bewegen mehr und mehr Unternehmen dazu, zu alternativen Datenbanken wie MongoDB oder NoSQL zu migrieren.
IBM Compose Enterprise delivers a fully managed cloud data platform on the public cloud of your choice - including IBM SoftLayer or Amazon Web Services (AWS) - so you can run MongoDB, Redis, Elasticsearch, PostgreSQL, RethinkDB, RabbitMQ and etcd in dedicated data clusters.
As enterprises work to replicate the development agility of internet companies and innovate in highly competitive markets, application development has grown increasingly complex. The large, monolithic codebases that traditionally power enterprise applications make it difficult to quickly launch new services. Siloed and potentially distributed development and operations teams present organizational alignment problems. On top of this, users are more demanding than ever – enterprises need to scale effectively and monitor deployments to ensure customers are provided with high performance and a consistent experience. Of course, all this needs to be done while providing always-on service availability.
MongoDB is an open-source, document database designed with both scalability and developer agility in mind. MongoDB bridges the gap between key-value stores, which are fast and scalable, and relational databases, which have rich functionality. Instead of storing data in rows and columns as one would with a relational database, MongoDB stores JSON documents with dynamic schemas.
Customers should consider three primary factors when evaluating databases: technological fit, cost, and topline implications. MongoDB's flexible and scalable data model, robust feature set, and high-performance, high-availability architecture make it suitable for a wide range of database use cases. Given that in many cases relational databases may also be a technological fit, it is helpful to consider the relative costs of each solution when evaluating which database to adopt.
The relational database has been the foundation of enterprise data management for over thirty years.
But the way we build and run applications today, coupled with unrelenting growth in new data sources and growing user loads are pushing relational databases beyond their limits. This can inhibit business agility, limit scalability and strain budgets, compelling more and more organizations to migrate to alternatives like MongoDB or NoSQL databases.
In a multi-database world, startups and enterprises are embracing a wide variety of tools to build sophisticated and scalable applications. IBM Compose Enterprise delivers a fully managed cloud data platform so you can run MongoDB, Redis, Elasticsearch, PostgreSQL, RethinkDB, RabbitMQ and etcd in dedicated data clusters.
Today, it’s unlikely that a single database will meet all your needs. For a
variety of reasons—including the need to support cloud-scale solutions
and increasingly dynamic app ecosystems—startups and enterprises
alike are embracing a wide variety of open source databases.
These varied databases—including MongoDB, Redis and PostgreSQL—
open doors to building sophisticated and scalable applications on
battle-hardened, non-proprietary databases.