Category Archives: NoSQL

Big Data, Memcached, NoSQL, Redis, Research

Redis/Memcached: Even Modest Datasets Can Enjoy the Speediest Performance

A pretty technical blog post over at Garantia Data’s blog relates the results of a recent benchmark test of the effects of cloud intrastructure on Memcached and Redis datasets:

Redis and Memcached were designed from the ground-up to achieve the highest throughput and the lowest latency for applications, and they are in fact the fastest data store systems available today. They serve data from RAM,  and execute all the simple operations (such as SET and GET) with O(1) complexity.

However, when run over cloud infrastructure such as AWS, Redis or Memcached may experience significant performance variations across different instances and platforms, which can dramatically affect the performance of your application.

Read the full post.


Consulting, Database, Linux, MySQL, NoSQL, Open Source, PostgreSQL

Bull Services Facilitate Adoption of Open Source PostgreSQL

Bull HN Information Systems is rolling out IT support services with the launch of its MOVE IT (Modernize, Optimize, Virtualize and Economize Information Technology) campaign to showcase products and services that it recently announced and plans to announce in the future. These products and services help customers derive maximum value from their legacy IT investments and get the most out of their IT operations while opening enterprise data to the cloud and mobile devices.

Bull’s newest MOVE IT service offerings are PostgreSQL support subscriptions; database design and build assessments; database performance and tuning services; and forms and reports migration services. These service offerings support migration to PostgreSQL—recognized as the world’s most advanced open source database—enabling organizations to reduce costs and open enterprise data to the cloud and virtualized environments.

According to Bull’s Data Migration Business Unit Director Jim Ulrey, “MOVE IT services and software help free companies from high licensing and maintenance costs, and offer both dramatic operational efficiencies and the agility required to flourish in competitive business environments.

“We developed MOVE IT enterprise solutions including database migration services, software and our newest support services to meet the needs of IT departments that prefer to manage work internally, as well as those that prefer to outsource—whether due to skill sets, resources or project objectives,” concluded Ulrey.

Bull’s MOVE IT products and services work effectively standalone by providing solutions to specific challenges, and they’re also engineered to work together to provide enterprise IT clients with multiple benefits. From cost-saving database migrations from Oracle to flexible open source PostgreSQL, to LiberTP™ software to migrate transaction-processing applications, Bull’s solutions open enterprise data to modern environments that support the cloud, virtualized environments and mobile devices. Most importantly, Bull can help free companies from high licensing and maintenance costs, offer dramatic operational efficiencies and the agility required to flourish in competitive business environments.


Guest Post, Memcached, NoSQL, Redis, Relational database management system

Taking In-Memory NoSQL to the Next Level

Guest Post by Ofer Bengal, Co-Founder & CEO, Garantia Data

 

Ofer Bengal

Ofer Bengal has founded and led companies in data communications, telecommunications, Internet, homeland security and medical devices.

Today Garantia Data is launching the first in-memory NoSQL cloud that promises to change the way people use Memcached and Redis. I think this is a great opportunity to examine the state of these RAM-based data stores and to suggest a new, highly-efficient way of operating them in the cloud.

Challenges of Cloud Computing

Memcached and Redis are being increasingly adopted by today’s web-applications, and are being used to scale-out their data-tier and significantly improve application performance (in many cases improvement is x10 over standard RDBMS implementation). However, cloud computing has created new challenges in the way scaling and application availability should be handled and using Memcached and Redis in their simple form may not be enough to cope with these challenges.

Memcached

It’s no secret Memcached does wonders for websites that need to quickly serve up dynamic content to a rapidly growing number of users. Facebook, Twitter, Amazon and YouTube, are heavily relying on Memcached to help them scale out; Facebook handles millions of queries per second with Memcached.
But Memcached is not just for giants. Any website concerned with response time and user based growth should consider Memcached for boosting its database performance. That’s why over 70% of all web companies, the majority of which are hosted on public and private clouds, currently use Memcached.

Local Memcached is the simplest and fastest caching method because you cache the data in the same memory as the application code. Need to render a drop-down list faster? Read the list from the database once, and cache it in a Memcached HashMap. Need to avoid the performance-sapping disk trashing of an SQL call to repeatedly render a user’s personalized Web page? Cache the user profile and the rendered page fragments in the user session.

Although local caching is fine for web applications that run on one or two application servers, it simply isn’t good enough when the data is too big to fit in the application server memory space, or when the cached data is updated and shared by users across multiple application servers and user requests. In such cases user sessions, are not bound to a particular application server. Using local caching under these conditions may end up providing a low hit-ratio and poor application performance.

Distributed Memcached tends to improve local caching by enabling multiple application servers to share the same cache cluster. Although the Memcached client and server codes are rather simple to deploy and use, Distributed Memcached suffers from several inherent deficiencies:

  • Lack of high-availability – When a Memcached server goes down the application’s performance suffers as all data queries are now addressed to the RDBMS, which is providing a much slower response time. When the problem is fixed, it could take between a few hours to several days until the recovered server becomes “hot” with updated objects and fully effective again. In more severe case, where session data is stored in Memcached without persistent storage, losing a Memcached server may cause forced logout of users or flush of their shopping carts (in ecommerce sites).
  • Failure hassle – The operator needs to set all clients for the replacement server and wait for it to “warm-up”. Operators sometimes add temporary slave servers to their RDBMS, for offloading their Master server, until their Memcached recovers.
  • Scaling hassle – When the application dataset grows beyond the current Memcached resource capacity, the operator needs to scale out by adding more servers to the Memcached tier. However, it is not always clear when exactly this point has been reached and many operators scale out in a rush only after noticing degradation in their application’s performance.
  • Scaling impact on performance – Scaling out (or in) Memcached typically causes partial or entire loss of the cached dataset, resulting, again, in degradation of the application’s performance.
  • Manpower – Operating Memcached efficiently requires manpower to monitor, optimize and scale when required. In many web companies these tasks are carried out by expensive developers or devops.

Amazon has tried to simplify the use of Memcached by offering ElastiCache, a cloud-based value-added service, where the user does not have to install Memcached servers but rather rent VMs (instances) pre-loaded with Memcached (at a cost higher than plain instances). However, ElastiCache has not offered a solution for any of the Memcached deficiencies mentioned above. Furthermore, ElastiCache scales-out by adding a complete EC2 instance to the user’s cluster, which is a waste of $$ for users who only require one or two more GBs of Memcached. With this model ElastiCache misses on delivery of the true promise of cloud computing – “consume and pay only for what you really need” (same as for electricity, water and gas).

Redis

Redis an open source, key-value, in-memory, NoSQL database began ramping-up in 2009 and is now used by Instagram, Pinterest, Digg, Github, flickr, Craigslist and many others and has an active open source community, sponsored by VMware.

Redis can be used as an enhanced caching system alongside RDBMS, or as a standalone database.
Redis provides a complete new set of data-types built specifically for serving modern web applications in an ultra-fast and more efficient way. It solves some of the Memcached deficiencies, especially when it comes to high availability, by providing replication capabilities and persistent storage. However, it still suffers from the following drawbacks:

  • Failure hassle – There is no auto-fail-over mechanism; when a server goes down, the operator still needs to activate a replica or build a replica from persistent storage.
  • Scalability – Redis is still limited to a single master server and although cluster management capability is being developed, it probably won’t be simple to implement and manage and will not support all Redis commands, making it incompatible with existing deployments.
  • Operations – Building a robust Redis system requires strong domain expertise in Redis replication and data persistence nuances and building a Redis cluster will be rather complex.
DB Caching Evolution

The Evolution of Caching

A new cloud service that will change the way people use Memcached and Redis

Imagine connecting to an infinite pool of RAM memory and drawing as much Memcached or Redis memory you need at any given time, without ever worrying about scalability, high-availability, performance, data security and operational issues; and all this, with the click of a button (ok, a few buttons). Now imagine paying only for GBs used rather than for full VMs and at a rate similar to what you pay your cloud vendor for plain instances. Welcome to the Garantia Data In-Memory NoSQL Cloud!  

By In-Memory NoSQL Cloud I refer to an online, cloud-based, in-memory NoSQL data-store service that offloads the burden of operating, monitoring, handling failures and scaling Memcached or Redis from the application operator’s shoulders. Here are my top 6 favorite features of such service, now offered by Garantia Data:

  • Simplicity – Operators will no longer need to configure and maintain nodes and clusters. The standard Memcached/Redis clients are set for the service DNS and from this moment on, all operational issues are automatically taken care of by the service.
  • Infinite scalability – The service provides an infinite pool of memory with true auto-scaling (out or in) to the precise size of the user’s dataset. Operators don’t need to monitor eviction rates or performance degradation in order to trigger scale-out; the system constantly monitors those and adjusts the user’s memory size to meet performance thresholds.
  • High availability – Built-in automatic failover makes sure data is guaranteed under all circumstances. Local persistence storage of the user’s entire dataset is provided by default, whereas in-memory replication can be configured at a mouse click. In addition, there is no data loss whatsoever when scaling out or in.
  • Improved application performance – Response time is optimized through consistent monitoring and scaling of the user’s memory. Several techniques that efficiently evict unused and expired objects are employed to significantly improve the hit-ratio.
  • Data security – For those operators who are concerned with hosting their dataset in a shared service environment, Garantia Data has full encryption of the entire dataset as a key element of its service.
  • Cost savings – Garantia Data frees developers from handling data integrity, scaling, high availability and Memcached/Redis version compliance issues. Additional savings are achieved by paying only for GBs consumed rather than for complete VMs (instances). The service follows the true spirit of cloud computing enabling memory consumption to be paid for much like electricity, water or gas, so you “only pay for what you really consume”.

We have recently concluded a closed beta trial with 20 participating companies where all these features were extensively tested and verified – and it worked fine! So this is not a concept anymore, it’s real and it’s going to change the way people use Memcached and Redis! Am I excited today? Absolutely!


GlassFish, Hosting, Java package, Jelastic, MongoDB, NoSQL, Platform as a service

ServInt Launches Jelastic Java Cloud Hosting Platform

ServInt, a provider of managed cloud hosting for enterprises worldwide, today announced the commercial availability of Jelastic, the world’s first software stack-agnostic, platform-as-a-service cloud hosting offering for Java applications. ServInt is the exclusive provider of Jelastic cloud hosting services in the United States, and the first service provider to offer Jelastic commercially.

ServInt’s Jelastic release follows the introduction last month of the ServInt Flex line of “dedicated cloud” servers, which combine the scalability advantages of cloud hosting with the sole-owner benefits of dedicated servers. ServInt now offers hosting products in both the IaaS and PaaS categories, with more cloud offerings and enhancements scheduled for release soon.

“This isn’t the first PaaS solution on the market – even for Java – but it’s the first one that leverages best-of-breed systems from both the hosting and the PaaS software industries,” said ServInt CEO Reed Caldwell. “The folks at Jelastic are amazing software developers. We are a world-class hosting provider. Too many PaaS providers try to be too many things to too many people, and that lack of focus makes them ineffective. We have collaborated directly with Jelastic every step of the way to ensure that Jelastic is the best designed, most reliable and best supported PaaS on the market.”

Jelastic COO Dmitry Sotnikov added, “Since we launched our public beta in October of last year, we have been growing at a rapid pace. Demand hasn’t slowed and the question of commercial availability has become even more frequent. Today, through our U.S. partner ServInt, Jelastic is now commercially available. This is a major step toward making our vision of a truly global, no lock-in, standards-based Java PaaS a reality.”

Unlike other Java PaaS and IaaS options on the market, Jelastic does not require customers to code to any specific API. Jelastic dynamically and instantaneously allocates resources for hosted applications, scaling servers up and down to make sure hosted apps have the resources they need, when they need them.

ServInt’s Jelastic customers are charged only for the actual RAM and CPU resources they consume, rather than for any predefined hosting service package or server they might otherwise purchase. This means hosting costs automatically go down when applications are off or not being used.

Jelastic measures resources being consumed in “cloudlets”, with one cloudlet equal to 128 MB of RAM and 200MHz of CPU processing power. Pricing is set at $0.02 per cloudlet/hour and there is no practical limit on the number of cloudlets that can be deployed. Jelastic does not require any application code changes. This means developers can simply upload their Java package or specify connection to their SVN or GIT code repository, and have their application running in the cloud in a few minutes – with no lock-in whatsoever.

Jelastic is fully compatible with all major Java software stacks, including Tomcat, GlassFish, Jetty and JBoss application servers – as well as with SQL (MariaDB, PostgreSQL, MySQL) and NoSQL (MongoDB, CouchDB) databases.