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Intel officially launches its beta program in partnership with Altibase and other IMDBs

Intel Optane DC Persistent Memory, what it is and how it works. Go to the beta program

Intel officially launches the beta program: hardware manufacturers and partner companies will be able to preview the new Intel Optane DC memories. What they are and why they are destined to change the storage market by speeding up the processing in the cloud

We have often talked about Intel Optane : it is a technology on which the Santa Clara company has invested so much and is increasingly being offered in our country too.
As explained in the Intel Optane Memory article or how to accelerate the performance of the system those currently available on the market are memory modules that drastically accelerate the performance of systems based on traditional hard drives and SATA SSDs .

Intel Optane DC Persistent Memory, what it is and how it works.  Go to the beta program

Although Intel has recently decided to take a step back and let Micron develop the XPoint 3D technology on which Optane is based ( Xpoint 3D technology will pass into Micron’s hands ), the company will continue to develop new products.

Intel Optane DC Persistent Memory is a bit considered as the evolution of Intel Optane Memory because it also combines skills aimed at the persistent preservation of data : Intel presents Optane DC memories that can be used both as RAM modules and as SSD .Today Intel has announced that it has started the “beta program” focused on Intel Optane DC Persistent Memory : this means that every cloud provider and every partner company (OEM) will be able to use a preview of the new memories that will be officially brought to the market during the first half year 2019 .

Thanks to the new Intel Optane DC Persistent Memory, combined with the new Xeon processors of the next generation, companies can revolutionize the ways in which heavy workloads, cloud processing, databases and high performance computing are managed: it becomes possible to bring performance to a much higher level, thanks to the ability to store and move data in memory quickly .

Intel Optane DC Persistent Memory, what it is and how it works.  Go to the beta program

Used in the App Dire mode , applications can count on performances never seen before thanks to the possibility of keeping in store, in a persistent way, an important amount of information. The Memory mode mode , however, allows you to use Intel Optane DC as a volatile memory using it as additional memory capacity than that offered by the RAM modules installed at the motherboard level.
It will thus be possible to have an additional, extremely fast, large storage capacity up to 512 GB . All this without the need to change a line of software side code.

Intel partner companies that have embraced Intel Optane DC Persistent Memory right from the start are Alibaba, Cisco, Dell EMC, Fujitsu, Google Cloud, Hewlett Packard Enterprise, Huawei, Lenovo, Oracle and Tencent.
Intel is also working with the most important software developers to optimize their solutions so they can take full advantage of using Intel Optane DC. The companies that have decided to join are, for the moment, Aerospike, Altibase, Apache Spark, AsiaInfo, Cassandra, DataBricks, Gigaspaces, IBM, Microsoft, Red Hat, RedisLabs, RocksDB, SAS, SAP, Sunjesoft, SuSE, Ubuntu, Virtuozzo and VMWare.

MEZMO adopts Altibase for its mobile app for the hearing impaired

Altibase Announces that MEZMO has Adopted Altibase for its Mobile Communication App for the Hearing Impaired

INNOCAPTION

Altibase is pleased to announce that MEZMO, the communication provider approved by the FCC as a TRS provider for the deaf in the US, has switched from MySQL to Altibase. Altibase will now function as its core database for telecommunication replay  service (TRS), which enables phone calls to the hearing impaired by showing the voice of the other party by letter.

MEZMO, headquartered in the US, operates the service, InnoCaption. The company found its MySQL database service inadequate in meeting its specific requirements. The challenges it was facing included performance deterioration as the number of subscribers increased and more services were added. Another issue was no real time updates of information on subscribers, billing status and logs. The process also requires some manual handling from time to time in batch mode. In addition, product instability, mediocre performance scaling and heavy dependence on add-ons of MySQL were often a cause for concern.

MEZMO required a database that could update and process its data without performance degradation. It also wanted to address the performance degradation issue with minimal investment in hardware additions or upgrade. The new database was required to allow for easy migration of data objects from MySQL and allow for easy adoption in the Amazon cloud. SQL databases, moreover, could pose problems with inter-operating with other systems built by the company on relational databases.

The above considerations were met by Altibase, and MEZMO adopted Altibase in 2014. Since then, Altibase has served MEMZO as a core database that provides both performance and reliability. MEZMO has been able to avoid performance degradation even when more subscribers and services are added.

Data processing and updating is now executed at a fraction of the cost that could have incurred with hardware addition for equal performance. Altibase’s hybrid architecture is utilized to store frequently used, recent data in memory, and less frequently used, historical data on disk.

The migration was easy and straightforward between relational databases, MySQL and Altibase.

MEZMO currently updates its system to analyze big data using Altibase in light of the performance and reliability Altibase has provided in the past 3 years.

After nearly 20 years as a closed source database, Altibase is now open source, and that includes its state-of-the-art sharding.

Learn more about Altibase at: https://youtu.be/pooexk0glK8, and download its open source database including sharding at: http://13.124.221.141.

 

In Memory Database Market – Key Players are Microsoft (U.S.), Oracle (U.S.), IBM (U.S), Altibase (U.S.) @Pragati Pathrotkar

In Memory Database Market – Key Players are Microsoft Corporation (U.S.), Oracle Corporation (U.S.), International Business Machines Corporation (U.S.), Altibase Corporation (U.S.)

A collection of data and filing the same in an organized manner is known as a database. When a software application interacts with databases, other applications and the user, to collect and analyze data, it is known as a database management system or DBMS. DBMS serves several purposes such as administration of databases, creation of data and updating of data among others. In memory database (IMDB) is a form of DBMS which utilizes the main memory of the device, for data storage. In memory database is also known as main memory database system (MMDB) or memory resistant database. When compared with disk optimized databases, the in memory database system functions much faster since it memory access is much faster than disk access. Most database management systems, such as Oracle, MySQL and Microsoft SQL Server utilize the mechanism of disk storage whereas in memory database systems, such as Oracle Coherence and Starcounter among others utilize the mechanism of memory access. In memory databases generally utilize volatile memory. But the introduction of non volatile memory modules has enabled the storage of data even in the event of power failure. Customized versions of in memory databases can offer several advantages. Some such advantages are the ability to accumulate and store large quantities of multidisciplinary data in a relational format, without having to wait for the slower batch processing and ability to predict events of find anomalies in data, by processing historical data and real-time data simultaneously.

PDF Brochure With Future Analysis @ https://www.transparencymarketresearch.com/sample/sample.php?flag=B&rep_id=20099b

The market for in memory database is primarily being driven by the growing demand for real-time monitoring of data and analytical data processing from most industry verticals. Industries such as e-commerce or retail has been more focused on gathering data on consumers for better understanding and predicting the purchasing behavior of the consumers. In line memory database strongly aids the organizations in performing the same and hence has been seeing good growth rate for the past few years. Additionally, the growth of internet-of-things connected devices has been promoting the growth of in memory databases market, since most of the infrastructure of IoT applications are being supported by these databases. Furthermore, the growing demand for advanced risk management solutions by various organizations has also been positively impacting the growth of in memory databases market. Considering the impact of all the factors mentioned above, the market for in memory databases can be expected to grow at a fast pace, during the forecast period from 2016 – 2024. The ongoing shift from in memory databases being a response time improver of analytical data processing to an enabler of online analytical processing (OLAP) / online transaction processing (OLTP) infrastructure is expected to offer unique opportunities for the in memory database market to grow.

Altibase provides better safety than Oracle TimesTen with minimum exposure to database corruption

How does Altibase compare to Oracle TimesTen and other in-memory databases?

Sep 13, 2018

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Altibase provides superior performance in comparison to Oracle TimesTen and other in-memory DBMSs. Representative examples include 99.999% HA, horizontal and vertical scalability, hybrid DB technology and more. When compared against Oracle TimesTen, Altibase excels in overall performance and especially in complex queries, and its data durability in system failure situations is more stable.

Altibase provides various communication channels (TCP/IP, SSL/TLS, Unix Domain Socket, IPC and IPC-DA) to optimize performance.

Altibase’s IPC-DA and Oracle TimesTen’s DA are similar in that both allow applications to directly read and write data to shared memory, which minimizes memory access and maximizes access performance. However, Altibase’s IPC-DA compares favorably to Oracle TimesTen’s DA because the former is safer than the latter. With Altibase’s IPC-DA, a client program accesses only a communication buffer, not data itself, so that it is not possible for the data to be exposed to corruption whereas Oracle TimesTen’s DA accesses a database directly so that data in the database is always potentially exposed to corruption.

Altibase has competed neck and neck particularly with Oracle TimesTen. The following case studies include related stories.

Altibase vs. Other In-Memory Databases

Category

Items

Altibase

Oracle TimesTen

IBM SolidDB

SAP HANA

Communication Channel

Direct Access

Supported

Supported

Not Supported

Not Supported

Lock Mechanism

MVCC

Supported

Supported

Supported

Supported

Functionality

SQL

SQL92, SQL99

SQL92, SQL99

SQL92, SQL99, SQL2003

SQL92, SQL99

Replication

Supported

Supported

Supported

Supported

Performance

(Complex Queries)

TPC-H

High performance

Low performance

Low performance

High performance

Productivity

Development

Convenience

APRE, PSM(PL/SQL)

ProC, PL/SQL

SA API, procedure

Precompiler Not offered, stored procedure

Usability

Management Tools

Orange

Oracle Enterprise Manager

Solid console

SPS 07

Platforms

Fully supported

Fully supported

Fully supported

Fully supported

Interactive SQL Tool

Supported

Supported

Supported

Supported

Storage Management

On-Disk Table

Supported

Not supported

Not supported

Not supported

Multiple DB Files Configuration

Supported

Not supported

Not supported

Supported

DB Autoextend

Supported

Not supported

Not supported

Supported

Replication

1:N way

Supported

Supported

Supported

Supported

Replication b/t Heterogeneous Systems

Supported

Supported

Supported

Supported

Replication Unit

Table

Table, database

Table

Table

Offline Replication

Supported

Not supported

Not supported

Not supported

Transaction

Save-Point

Supported

Supported

Supported

Supported

Rollback

Supported

Supported

Supported

Supported

Stability

DB Backup

Offline, online, logical, incremental

Offline, online, logical, incremental

Offline, online, logical backup

Offline, online, logical backup

Range of Data Recovery

Transaction, media,
system failure

Transaction, media,
system failure

Transaction, media,
system failure

Transaction, media,
system failure

Interface

Embedded SQL

Supported

Supported

Supported

Supported

ODBC

Supported

Supported

Supported

Supported

JDBC

Supported

Supported

Supported

Supported

XA API

Supported

Supported

Supported

Not supported

SQLCLI

Supported

Supported

Supported

Not Supported

C API

Supported

Supported

Supported

Not Supported

Advanced SQL

SQL Plan Cache

Supported

Not supported

Not supported

Supported

Queue Table

Supported

Not supported

Not supported

Not supported

DB Link

Supported

Not supported

Not supported

Supported

 

Altibase – Downloading is Believing.

What is sharding? @Alexander Lielacher

What Is Sharding?

 by 

What Is Sharding?

Sharding is a concept in database design, and as implied by its name, sharding involves creating smaller parts from a larger one. In the context of databases, sharding results in the creation of smaller partitions in the ledger. These partitions are thus referred to as shards.

It is important to note that in sharding, the partitioning is done horizontally as opposed to vertically. A shard may contain data that is in all the other shards; however, these partitions are designed to include data that is accessible only through it, which means that the data in each shard is unique to it. To access the data and use it, one must queue the specific shard that contains said data.

Sharding is employed in database architecture because it can improve the performance of a database or search engine. The design tool does this because it reduces the index size of a ledger. As a result, the ledger can provide search results quicker. Additionally, because different shards can be stored on different servers, the tool can be beneficial for large corporations with large data sets that they need to store separately such as multinational corporations operating in different countries.

Sharding in Distributed Ledgers

Sharding has grown in popularity within the cryptocurrency community as a result of widespread concerns over blockchain scalability issues. For instance, the Bitcoin Network processes about seven transactions per second, and Ethereum is only slightly faster, handling around 15 operations per second. These are both paltry compared to large payment processors like Visa and Mastercard.

While the bitcoin community has dealt with its scaling issues in various ways, the Ethereum project has outlined a more streamlined approach to solving its scalability concerns. Ethereum’s approach involves switching to a Proof of Stake (PoS) algorithm, which will work in tandem with a sharded database design.

How Would Sharding Work on Ethereum?

During his keynote speech at an event held at the School of Business of the Singapore University of Social Sciences, Ethereum’s cocreator Vitalik Buterin attempted to explain the concept of sharding the Ethereum ledger in a straightforward manner. In his talk entitled “The Road Ahead,” he stated:

“Imagine that Ethereum has been split into thousands of islands. Each island can do its own thing. Each of the islands has its own unique features and everyone belonging on that island, i.e., the accounts, can interact with each other and they can freely indulge in all its features. If they want to contact with other islands, they will have to use some sort of protocol.”

Currently, on the Ethereum network, as well as other blockchains, each node stores the global state. The globals state refers to the account balances, contract code and storage and all additional relevant information. Additionally, all nodes process all transactions. While this provides for a very secure ledger, it dramatically limits to what extent the network can scale because, within this design, a blockchain is only as good as a single node on its network.

In other words, the speed of a blockchain is defined by how quick a single node is as all nodes must perform the same transaction over and over.