about
aboutAbout us

Transaction isolation is one of the most fundamental fea- tures offered by a database management system (DBMS). It provides the user with the illusion of being alone in the da- tabase system, even in the presence of multiple concurrent users, which greatly simplifies application development. In the background, the DBMS ensures that the resulting con- current access patterns are safe, ideally by being serializable.

This is an extremely desirable property and the reason why many DBMSs implement MVCC, e.g., Oracle, Microsoft SQL Server, SAP HANA, and PostgreSQL. However, most systems that use MVCC do not guarantee serializability, but EinsteinDB takes care of this by exploiting a multi-layered relativistic linearizable multi-stores. With EinsteinDB and MilevaDB, every transaction sees the database in a certain state (typically the last committed state at the beginning of the transaction) and the Noether ensures that two concurrent transactions do not update the same data object..

  • a simpler interface to RDMA and other remote memory technologies compared to the existing verbs interfaceabout
  • You can use our Multi-raft BFT with VioletaBFT harnessing both rust-protobuf or Prost to encode/decode gRPC messagesabout
  • Statistical analysis detects if, and by how much, performance has changed since the last benchmark runabout
  • Automate the syntatic conversion of Haskell into Rust for JIT PostgresQL Hybrid OLAP/OLTPabout

a new database engine optimized for memory resident data and Hybrid OLTP workloads. EinsteinDB is fully integrated into SQL Server; it is not a separate system. To take advantage of EinsteinDB's Causets, a user simply declares a table memory optimized locally, not globally.

More About Us
about
fun

P95 latency (QoS)

Online Serving Latency less than 5ms

fun

250,000

predictions per second

fun

100 Petabytes

Avg OLTP/OLAP client workload

fun

268.74

D.MB/s CPU: Skylake i7-6700 3.4 GHz

EinsteinDB is a new join engine architecture, with which it introduces a novel query optimizer with MilevaDB and data layouts that leverage single-instruction multiple with FIDel IBM's inspired tuplespace timeshare. data (SIMD) parallelism

the per packet processing times with EinsteinDB Moscovium Enterprise and Top Secret GHD. Experiencing a median times for traditional NAT and load balancer from 2.07µs to 2.25µs at peak times, respectively.

services

EinsteinDB, MilevaDB and BerolinaSQL provide a novel HTAP query compiler based on generalized hypertree decompositions (GHDs): opportunistically increasing the amount of available SIMD parallelism in the set intersection operation

Many SaaS applications—especially B2B apps—are multi tenant. So the apps have a natural dimension on which to distribute data across nodes: just shard by tenant_id. Our EinsteinDB Californium Enterprise extension to Postgres enables you to scale out your database to millions of tenants, without having to re-architect your application.

Learn More
services
services

Partitions are further broken into “chunks” that are stored in a decomposed storage model in “attribute vectors” with each attribute vector stored on a different virtual memory (VM) page.

EinsteinDB has a relativistic causal consistent management scheme capable of identifying timelike transactional data (cold), separating it from the timelike data (hot), and compressing it in a read-optimized format for OLAP queries.

Learn More
services
services

After clustering the data, the database system compresses cold chunks to reduce memory consumption and streamline query processing.

Cold chunks are stored on huge virtual memory pages and protected from any modifications to allow for compact and fast OLAP snapshots.

Learn More
services
services

New Data lives in Cones: Hot and Warm Buckets but appended from their adjacent root vertex.

• 800+ IOPS for Standard Workloads • 1200+ IOPS for Heavy Workloads. ▶ Data rolls from Timelike (Cold) to TimelikeNull(Frozen) when The total size of the index (Lightlike+Spacelike+Lightlike) grows too large wherein The oldest event in a bucket exceeds a specific age.

Learn More
services
chooseWhy Choose Us

Outstanding Digital Experience

Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna.

1

Best Performence

Dolor sit amet consectetur elit eiusmod tempor incidi dunt labore dolore magna aliqua enim.

2

Dedicated Team Member

Dolor sit amet consectetur elit eiusmod tempor incidi dunt labore dolore magna aliqua enim.

3

24/7 Support

Dolor sit amet consectetur elit eiusmod tempor incidi dunt labore dolore magna aliqua enim.

choose

What Our Clients are Saying?

Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna.

testimonials
testimonials

Our Affordable Pricing Plans

Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna.

Weekly Plan

$ 120 / Per week
  • SEO & Branding
  • Digital Marketing
  • Google Analytics
  • Branding Solutions
  • Digital Accounts
  • Pay-per-Click
  • 24/7 Support

Month Plan

$ 840 / Per month
  • SEO & Branding
  • Digital Marketing
  • Google Analytics
  • Branding Solutions
  • Digital Accounts
  • Pay-per-Click
  • 24/7 Support

Yearly Plan

$ 3,600 / Per yearly
  • SEO & Branding
  • Digital Marketing
  • Google Analytics
  • Branding Solutions
  • Digital Accounts
  • Pay-per-Click
  • 24/7 Support
testimonialsTeam Members

Our Awesome Team

Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna.

testimonials

Merv Adrian

CEO & Founder
testimonials

Kirk Borne

UX/UI Designer
testimonials

Carla Gentry

Web Developer
analysis
Analysis

Scalable memory allocation using jemalloc

In general-purpose applications, most data is dynamically allocated. The memory manager therefore plays a crucial role in application performance by determining the spatial locality of heap objects.

partner
partner
partner
partner
partner
partner
Our Blog

Bipartite Embedded Semi-Relational In-Memory Relativistic Cache Policies at CloudKitchens

The SSD cost per IO/s is surprisingly uniform across hardware vendors in the range of $0.05-0.10 per read IO/s, while server class DRAM costs around $15/GB. Therefore, the break-even point for a 200 byte record is about 60 minutes, while for a traditional 4kB page is about 3 minutes.

partner
partner