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General purpose, extendible backend platform for making diverse and powerful solutions across diverse domains

Elasticgraph (EG) is an innovative and powerful offering by Mindgrep. It is meant to empower the core of your tech solution - with respect to your database, content or asset related needs. It is world's first solution to provide multilingual and relationship aware features like storage, management, semantic tagging, join based retrieval, file metadata, and content extraction, full-text graph search, file search, graph analytics, team collaboration, publishing, etc. It runs as an application middle layer in front of an Elasticsearch cluster and is integrable with all other sources or destinations where your data, content or assets are stored or managed - forex. databases, DMS, DAM, CMS, cloud drives, hard drives, network storage, etc. EG uses [Elasticsearch stack] to provide the actual data storage, basic full-text search, analytics and more. EG middle layer extends Elasticsearch to provide more capability and power functionality, through its JSON API and unique management and administration Dashboard. Riding on the shoulder of open source giants like Elasticsearch, FFmpeg, LibreOffice, EG completes the circle of a typical modern organization's or startup's various requirements. EG comes as hosted service and partly on a license basis. The Elasticsearch cluster can be maintained by Mindgrep or you wherever you prefer. EG can work to and fro with diverse locations, apps and services, either privately managed or running somewhere on cloud or world wide web. It is designed such that your solution goes live and you can iterate fast, and your team can manage your backend & workflows easily & effectively. Given the multifaceted value, EG can provide to any organization small, medium or large, it is a must-have of the technology infrastructure for any modern organization. And you know what- we @ Mindgrep will make sure you have a cost-effective solution compared to all other comparable services in the industry.

 

Purposes

Relation aware Nosql datastore w/ deep joins

Content, file & asset management

Full text graph search
"Give me friends of friends who live in Bangalore"

Graph analytics and machine learning
"Give me country wise count of friends of friends."

Highlights

  • General purpose, an extendible platform for solving diverse needs across diverse domains
  • Elasticsearch based data storage backend - world's leading opensource search, analytics solution, also NoSQL datastore
  • Performance at scale over big data and concurrent usage
  • Is low on hardware network requirements, thus saving significant hosting cost, while giving a power punch of performance.
  • Comes with customization services to fulfill custom needs from diverse domains and use cases.
  • API service with data storage is hosted by Mindgrep.
  • You have the choice to host the Elasticsearch cluster yourself.
  • JSON API (a superset of ES API) for powering your apps or solutions
  • Better retrieval performance at scale and complexity, than pure ES, which is faster than most or all database/search solutions in the industry.
  • Best in industry performance for the graph (relational) search and analytics/ML operations
  • The application layer abstractions of EG are designed to do most of the spadework for developers in typical applications, simplify complex queries, improve code quality & improve developer efficiency by a significant margin.
  • Improves team efficiency in managing, securing and retrieving data, content & digital or physical assets
  • Integrable with other niche services through API so that all your requirements can be fulfilled in a holistic way.

Comparison Chart

  A   B C D E F G H I
1
    Elasticsearch EG Mongodb Mysql Neo4j Sample DAM MAYAN Google Drive
2
Service   Database management, search, analytics General purpose platform for management, search, analytics and retrieval of database, content and assets. Database management, analytics Database management Database management, search, analytics DAM for publishing and marketing DMS on premise DMS with hosted cloud store
3
Is a platform   N (Is a database management, search, analytics engine) Y (Has a broad array of applications, by itself or in integration with other services) N (Is a database) N (Is a database) N (Is a database) N (Is a service designed for specific job related to content publishing and marketing) N (Deals with files on your physical storage somewhere. ) N
4
Can work as single source of Truth of all data, content and assets, integrable with other services   N Y (Can be integrated back and forth with cloud drives, DMS, DAM, CMS, Social Network, any kind of data, content or asset sources) N N N Y, N (Some DAMs aim to provide single source of truth for assets, but none do it for data) N (Deals with files on your physical storage somewhere. ) N
5
Datastorage   Y - JSON Y - JSON (WIth ES as its datastore) Y - JSON like BSON Y - Columnar Y - Property Graph N/A N N
6
Archive management   N Y (Can be the heart of your archive management, in integration with all the places where your content and assets are to be found or published) N N N N Y, N (can be part of solution for archive management, since it handles only hard disk storage in your control) Y, N (can be part of solution for archive management, since it provides cloud storage with versioning, history, collaborative features etc)
7
Digital Asset Management (DAM)   N/A Y (Can manage any kind of assets like text, audio, video, images, other kinds of files, for any domain or use case. Is not specific to any domain but customisable and extendible.) N/A N/A N/A Y (But most known DAMs are designed specifically for publishing and marketing images and videos only) Y (Lets you manage anything you store on a hard drive managed by the DMS) Y (Lets you manage anything you store on a hard drive managed by the DMS)
8
Multilingual   N Y (data storage, admin UI and API, everything is multilingual) N N N N N/A N/A
9
File storage   Y, N (As blobs in DB) Y, N (As blobs in DB, but can sync, scan and work with other file stores) Y, N (As blobs in DB) Y, N (As blobs in DB) N (Not really designed to search within files) Y (Manages files on its cloud storage) Y (Manages files on your physical storage managed by you) Y (Manages files on your physical storage managed by you)
10
Relationship aware JSON database management   N Y (Advanced, in depth) N Y (Simpler, less depth) Y (Advanced, in depth) N/A N/A N/A
11
Joins at deep relationship depth   N Y N Y Y N/A N/A N/A
12
Full text search with ranking   Y Y N N Y, N (if integrated with ES) N/A N/A N/A
13
Graph (relationship based) search over database   N Y N N Y N/A N/A N/A
14
Aggregations/Analytics over entities   Y (Perhaps fastest and most complete) Y (Everything ES can do) Y Y Y N/A N/A N/A
15
Graph analytics (over data of related entities).   N Y (Exends ES with relationship based analytics) N N Y (but perhaps not as fast as EG) N/A N/A N/A
16
Ease of expressing complex queries (like the one above)   N Y N N Y N/A N/A N/A
17
Admin user Interface for data administration, meta tagging, cataloging, management by backend team   N Y (Multi lingual, fully customisable and user friendly) N N N N/A N/A N/A
18
Data dependency rules like
(file.processingStatus = parentFolder.processingStatus)
  N Y N N N N/A N/A N/A
19
Transaction support   N (A compromise, for fast performance) N (A compromise, for fast performance) Y (Since 4.0) Y (Is a must for the parts of application flow where you necessarily require transactions) Y N/A N/A N/A
20
Suitable for search and recommendations needs   Y (Made exactly for that. But provides this just over JSON document fields) Y (extends ES search over JSON documents, to configurably include relationship data within the JSON documents for graph search) N (Not part of design by intention) N (Not part of design by intention) Y (make use of relationships and data, but different way of expressing queries than EG) N/A N/A N/A
21
Scans and syncs files and folders on hard drives   N Y N N N Y Y Y
22
Can integrate with diverse type of file storage locations on cloud, 3rd party services, DMS etc.   N/A Y N/A N/A N/A Y (They generally have APIs) N (Works only with one location which it manages) N (Works only with one location which it manages)
23
Browse directories and files by any scanned storage location   N Y N N N N/A Y Y
24
Extract, stores and indexes file metadata of audio, video, image, text files for search   N Y (by scanning hard drives or other storage locations or services) N N N Y N (Extracts very basic metadata, and is not made primarily for indexing and search) N (Extracts very basic metadata, and is not made primarily for indexing and search)
25
Search files based on their text content   Y (Developer has to implement this feature) Y (scans files and indexes text content in ES) N N Y, N (if integrated with ES) N N N
26
Search files based on their metadata   N Y (indexes file's basic and technical metadata) N N N Y N (Extracts very basic metadata, and is not made primarily for indexing and search) N (Extracts very basic metadata, and is not made primarily for indexing and search)
27
Search files based on text tags ,keywords   N Y (As intentional part of solution) N N N Y Y, N (Only pure text keyword search) N
28
Search files based on data of related entities   N Y (As intentional part of solution) N N N N N N
29
Admin user Interface for content and asset management, meta tagging, cataloging, search, browsing by backend team   Y N N N N Y Y N
30
Versioning and history of files   N/A Y, N (Needs to work with a DMS or DAM to maintain history and versioning) N/A N/A N/A Y Y Y
31
Scale with big data and high concurrency   Y (As intentional part of solution) Y (As intentional part of solution) Y (As intentional part of solution. But hogs memory.) N (Not especially known for its performance) Y N/A N/A N/A
32
Find and retrieve content and assets   N Y (Through keywords, metadata and relationships) N N N Y (Through keywords and metadata) Y Y
33
Login based access   Y Y Y Y Y Y Y Y
34
Role and rule based access   Y, N (Partially in FOSS, Full in commercial license) Not yet, but planned. Y Y Y Y Y Y
35
Scalability a primary goal at heart of the solution   Y (Built to scale horizontally with ease) Y (Both ES and EG have optimimisations to perform well together, under high load of concurrent requests and large size of data) Y (But in our opinion not as beautifully scalable, less resource consuming and well performing as ES) N (It is slowest and more difficult to manage at scale, of the lot considered here) Y (The website mentions performance at scale, but we do not have experience with it so far, to compare) Y N/A (Built for marketing purposes where scalability is not a faced challenge) N/A (Built for marketing purposes where scalability is not a faced challenge)
36
Is open source   Y, N (Partially in FOSS, Partly commercial) N Y, N (Partially in FOSS, Partly commercial) Y N N Y N
37
Ships as   FOSS, Hosted services Hosted service. ES datastore can be hosted by you or Mindgrep. Part of software related to file management is licensed and runs on archive premise FOSS, Hosted services FOSS, Hosted services Commercial License Hosted service FOSS, hosted on premise FOSS, hosted on premise
38
Customisability   Y (The whole application layer is written by you) Y (Designed to be fully customisable for diverse domains and use cases) Y (The whole application layer is written by you) Y (The whole application layer is written by you) Y (The whole application layer is written by you) Y, N (Limited to publishing and marketing domain) Y, N (Customisability is only in roles and permissions of team which are set by you) Y, N (Customisability is only in roles and permissions of team which are set by you)