Apache TinkerPop

Apache TinkerPop

Apache Software Foundation
GraphBase

GraphBase

FactNexus

About

Apache TinkerPop™ is a graph computing framework for both graph databases (OLTP) and graph analytic systems (OLAP). Gremlin is the graph traversal language of Apache TinkerPop. Gremlin is a functional, data-flow language that enables users to succinctly express complex traversals on (or queries of) their application's property graph. Every Gremlin traversal is composed of a sequence of (potentially nested) steps. A graph is a structure composed of vertices and edges. Both vertices and edges can have an arbitrary number of key/value pairs called properties. Vertices denote discrete objects such as a person, a place, or an event. Edges denote relationships between vertices. For instance, a person may know another person, have been involved in an event, and/or have recently been at a particular place. If a user's domain is composed of a heterogeneous set of objects (vertices) that can be related to one another in a multitude of ways (edges).

About

GraphBase is a Graph Database Management System (Graph DBMS) engineered to simplify the creation and maintenance of complex data graphs. Complex and highly-connected structures are a challenge for the Relational Database Management System (RDBMS). A graph database provides much better modelling utility, performance and scalability. The current crop of graph database products - the triplestores and property graphs - have been around for nearly two decades. They're powerful tools, they have many uses, but they're still not suited to the management of complex data structures. With GraphBase, our goal was to simplify the management of complex data structures, so that your data could become something more. It could become Knowledge. We achieved this by redefining how graph data should be managed. In GraphBase, the graph is a first-class citizen. You get a graph equivalent of the "rows and tables" paradigm that makes a Relational Database so easy to use.

About

StarTree, powered by Apache Pinot™, is a fully managed real-time analytics platform built for customer-facing applications that demand instant insights on the freshest data. Unlike traditional data warehouses or OLTP databases—optimized for back-office reporting or transactions—StarTree is engineered for real-time OLAP at true scale, meaning: - Data Volume: query performance sustained at petabyte scale - Ingest Rates: millions of events per second, continuously indexed for freshness - Concurrency: thousands to millions of simultaneous users served with sub-second latency With StarTree, businesses deliver always-fresh insights at interactive speed, enabling applications that personalize, monitor, and act in real time.

About

Simple, fast, safe, and compiled. For developing maintainable software. Simple language for building maintainable programs. You can learn the entire language by going through the documentation over a weekend, and in most cases, there's only one way to do something. This results in simple, readable, and maintainable code. This results in simple, readable, and maintainable code. Despite being simple, V gives a lot of power to the developer and can be used in pretty much every field, including systems programming, webdev, gamedev, GUI, mobile, science, embedded, tooling, etc. V is very similar to Go. If you know Go, you already know 80% of V. Bounds checking, No undefined values, no variable shadowing, immutable variables by default, immutable structs by default, option/result and mandatory error checks, sum types, generics, and immutable function args by default, mutable args have to be marked on call.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Developers seeking a solution to manage their graph databases and graph analytic systems

Audience

Companies and developers interested in a graph database management system solution optimize the creation and maintenance of complex data graphs

Audience

Companies with up to petabytes of data needing to run high queries-per-second (QPS) workloads

Audience

Developers interested in a language for building maintainable programs

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Apache Software Foundation
United States
tinkerpop.apache.org

Company Information

FactNexus
Founded: 2010
Australia
graphbase.ai/

Company Information

StarTree
Founded: 2019
United States
www.startree.ai

Company Information

V Programming Language
United States
vlang.io

Alternatives

Alternatives

Alternatives

CelerData Cloud

CelerData Cloud

CelerData

Alternatives

Swift

Swift

Apple
InfiniteGraph

InfiniteGraph

Objectivity
Zig

Zig

Zig Software Foundation

Categories

Categories

Categories

Categories

Big Data Features

Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates

Data Analysis Features

Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics

Database Features

Backup and Recovery
Creation / Development
Data Migration
Data Replication
Data Search
Data Security
Database Conversion
Mobile Access
Monitoring
NOSQL
Performance Analysis
Queries
Relational Interface
Virtualization

Streaming Analytics Features

Data Enrichment
Data Wrangling / Data Prep
Multiple Data Source Support
Process Automation
Real-time Analysis / Reporting
Visualization Dashboards

Integrations

Amazon Redshift
Amazon S3
Apache Flink
Apache Groovy
Apache Kafka
Apache Pulsar
C
Confluent
Databricks Data Intelligence Platform
Delta Lake
Docker
Embeddable
G.V() - Gremlin IDE
Google Cloud BigQuery
Hadoop
Helix Editor
Java
Lapce
MySQL
Tableau

Integrations

Amazon Redshift
Amazon S3
Apache Flink
Apache Groovy
Apache Kafka
Apache Pulsar
C
Confluent
Databricks Data Intelligence Platform
Delta Lake
Docker
Embeddable
G.V() - Gremlin IDE
Google Cloud BigQuery
Hadoop
Helix Editor
Java
Lapce
MySQL
Tableau

Integrations

Amazon Redshift
Amazon S3
Apache Flink
Apache Groovy
Apache Kafka
Apache Pulsar
C
Confluent
Databricks Data Intelligence Platform
Delta Lake
Docker
Embeddable
G.V() - Gremlin IDE
Google Cloud BigQuery
Hadoop
Helix Editor
Java
Lapce
MySQL
Tableau

Integrations

Amazon Redshift
Amazon S3
Apache Flink
Apache Groovy
Apache Kafka
Apache Pulsar
C
Confluent
Databricks Data Intelligence Platform
Delta Lake
Docker
Embeddable
G.V() - Gremlin IDE
Google Cloud BigQuery
Hadoop
Helix Editor
Java
Lapce
MySQL
Tableau
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