DBMS > Bangdb vs. Faircom EDGE vs. Greenplum vs. Infobright vs. PostgreSQL
System Properties Comparison Bangdb vs. Faircom EDGE vs. Greenplum vs. Infobright vs. PostgreSQL
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Name | Bangdb Xexclude from comparison | Faircom EDGE formerly c-treeEDGE Xexclude from comparison | Greenplum Xexclude from comparison | Infobright Xexclude from comparison | PostgreSQL Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Converged and high performance database for device data, events, time series, document and graph | FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments | Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image. | High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Document store Graph DBMS Time Series DBMS | Key-value store Relational DBMS | Relational DBMS | Relational DBMS | Relational DBMS with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Spatial DBMS | Document store Spatial DBMS | Document store Graph DBMS with Apache Age Spatial DBMS Vector DBMS with pgvector extension | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | bangdb.com | www.faircom.com/products/faircom-edge | greenplum.org | ignitetech.com/softwarelibrary/infobrightdb | www.postgresql.org | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | docs.bangdb.com | docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html | docs.greenplum.org | www.postgresql.org/docs | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Sachin Sinha, BangDB | FairCom Corporation | Pivotal Software Inc. | Ignite Technologies Inc.; formerly InfoBright Inc. | PostgreSQL Global Development Group www.postgresql.org/developer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2012 | 1979 | 2005 | 2005 | 1989 1989: Postgres, 1996: PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | BangDB 2.0, October 2021 | V3, October 2020 | 7.0.0, September 2023 | 16.3, May 2024 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source BSD 3 | commercial Restricted, free version available | Open Source Apache 2.0 | commercial The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016 | Open Source BSD | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Implementation language | C, C++ | ANSI C, C++ | C | C | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | Linux | Android Linux ARM, x86 Raspbian Windows | Linux | Linux Windows | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | schema-free | Flexible Schema (defined schema, partial schema, schema free) | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes: string, long, double, int, geospatial, stream, events | yes, ANSI Standard SQL Types | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
XML support Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT. | no | yes | yes since Version 4.2 | no | yes specific XML-type available, but no XML query functionality. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes secondary, composite, nested, reverse, geospatial | yes | yes | no Knowledge Grid Technology used instead | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | SQL like support with command line tool | yes ANSI SQL queries | yes | yes | yes standard with numerous extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | Proprietary protocol RESTful HTTP API | ADO.NET Direct SQL IoT Microservice layer JDBC MQTT (Message Queue Telemetry Transport) ODBC RESTful HTTP API | JDBC ODBC | ADO.NET JDBC ODBC | ADO.NET JDBC native C library ODBC streaming API for large objects | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | C C# C++ Java Python | C C# C++ Java JavaScript PHP Python VB.Net | C Java Perl Python R | .Net C C# C++ D Eiffel Erlang Haskell Java Objective-C OCaml Perl PHP Python Ruby Scheme Tcl | .Net C C++ Delphi Java JDBC JavaScript (Node.js) Perl PHP Python Tcl | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | no | yes .Net, JavaScript, C/C++ | yes | no | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes, Notifications (with Streaming only) | yes | yes | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm | File partitioning Customizable business rules for partitioning | Sharding | none | partitioning by range, list and (since PostgreSQL 11) by hash | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | selectable replication factor, Knob for CAP (enterprise version only) | yes Synchronous and asynchronous realtime replication based on transaction logs | Source-replica replication | Source-replica replication | Source-replica replication other methods possible by using 3rd party extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no | no | yes | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Tunable consistency, set CAP knob accordingly | Immediate Consistency Tunable Consistency | Immediate Consistency | Immediate Consistency | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | yes when using SQL | yes | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | ACID | ACID | ACID | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes, optimistic concurrency control | yes across SQL and NoSQL | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes, implements WAL (Write ahead log) as well | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes, run db with in-memory only mode | yes | no | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | yes (enterprise version only) | Fine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL. | fine grained access rights according to SQL-standard | fine grained access rights according to SQL-standard exploiting MySQL or PostgreSQL frontend capabilities | fine grained access rights according to SQL-standard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Bangdb | Faircom EDGE formerly c-treeEDGE | Greenplum | Infobright | PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | PostgreSQL is the DBMS of the Year 2023 Snowflake is the DBMS of the Year 2022, defending the title from last year Snowflake is the DBMS of the Year 2021 Innovative Software and Giant Lego Sets, Why FairCom Edge Booth is a Must-Visit at Automate Data Technology Company FairCom Expands The Edge with 2 New Releases of its Edge Computing Products Brokers, Protocols, Platform Move Manufacturing Data FairCom kicks off new era of database technology USA - English World's First Converged IIoT Hub to be Showcased at IoT Tech Expo provided by Google News VMware Greenplum on AWS: Parallel Postgres for Enterprise Analytics at Scale | Amazon Web Services 1. Introducing the Greenplum Database - Data Warehousing with Greenplum [Book] RSA: EMC integrates Hadoop with Greenplum database Greenplum 6 ventures outside the analytic box Greenplum 6 review: Jack of all trades, master of some provided by Google News Ignite Buys Database Vendor Infobright provided by Google News How LeadSquared accelerated chatbot deployments with generative AI using Amazon Bedrock and Amazon Aurora ... EDB unveils EDB Postgres AI Introducing OCI Database with PostgreSQL: Completing Our Cloud Database Suite for Every Need Why PostgreSQL Is the Bedrock for the Future of Data General availability: Microsoft Entra ID integration with Azure Cosmos DB for PostgreSQL | Azure updates provided by Google News |
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