DBMS > Faircom DB vs. HEAVY.AI vs. Hypertable vs. Manticore Search vs. PostgreSQL
System Properties Comparison Faircom DB vs. HEAVY.AI vs. Hypertable vs. Manticore Search vs. PostgreSQL
Editorial information provided by DB-Engines | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Name | Faircom DB formerly c-treeACE Xexclude from comparison | HEAVY.AI Formerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022 Xexclude from comparison | Hypertable Xexclude from comparison | Manticore Search Xexclude from comparison | PostgreSQL Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs. | A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware | An open source BigTable implementation based on distributed file systems such as Hadoop | Multi-storage database for search, including full-text search. | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Key-value store Relational DBMS | Relational DBMS | Wide column store | Search engine | 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 | Time Series DBMS using the Manticore Columnar Library | Document store Graph DBMS with Apache Age Spatial DBMS Vector DBMS with pgvector extension | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | www.faircom.com/products/faircom-db | github.com/heavyai/heavydb www.heavy.ai | manticoresearch.com | www.postgresql.org | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html | docs.heavy.ai | manual.manticoresearch.com | www.postgresql.org/docs | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | FairCom Corporation | HEAVY.AI, Inc. | Hypertable Inc. | Manticore Software | PostgreSQL Global Development Group www.postgresql.org/developer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 1979 | 2016 | 2009 | 2017 | 1989 1989: Postgres, 1996: PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | V12, November 2020 | 5.10, January 2022 | 0.9.8.11, March 2016 | 6.0, February 2023 | 16.3, May 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | commercial Restricted, free version available | Open Source Apache Version 2; enterprise edition available | Open Source GNU version 3. Commercial license available | Open Source GPL version 2 | Open Source BSD | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Implementation language | ANSI C, C++ | C++ and CUDA | C++ | C++ | C | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | AIX FreeBSD HP-UX Linux NetBSD OS X QNX SCO Solaris VxWorks Windows easily portable to other OSs | Linux | Linux OS X Windows an inofficial Windows port is available | FreeBSD Linux macOS Windows | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | schema free, schema optional, schema required, partial schema, | yes | schema-free | Fixed schema | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes, ANSI SQL Types, JSON, typed binary structures | yes | no | Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean | 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 | no | Can index from XML | yes specific XML-type available, but no XML query functionality. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | no | restricted only exact value or prefix value scans | yes full-text index on all search fields | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | yes, ANSI SQL with proprietary extensions | yes | no | SQL-like query language | yes standard with numerous extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | ADO.NET Direct SQL JDBC JPA ODBC RESTful HTTP/JSON API RESTful MQTT/JSON API RPC | JDBC ODBC Thrift Vega | C++ API Thrift | Binary API RESTful HTTP/JSON API RESTful HTTP/SQL API SQL over MySQL | ADO.NET JDBC native C library ODBC streaming API for large objects | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | .Net C C# C++ Java JavaScript (Node.js and browser) PHP Python Visual Basic | All languages supporting JDBC/ODBC/Thrift Python | C++ Java Perl PHP Python Ruby | Elixir Go Java JavaScript (Node.js) Perl PHP Python | .Net C C++ Delphi Java JDBC JavaScript (Node.js) Perl PHP Python Tcl | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | yes .Net, JavaScript, C/C++ | no | no | user defined functions | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes | no | no | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | File partitioning, horizontal partitioning, sharding Customizable business rules for table partitioning | Sharding Round robin | Sharding | Sharding Partitioning is done manually, search queries against distributed index is supported | partitioning by range, list and (since PostgreSQL 11) by hash | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution). | Multi-source replication | selectable replication factor on file system level | Synchronous replication based on Galera library | 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 | Eventual Consistency Immediate Consistency Tunable consistency per server, database, table, and transaction | Immediate Consistency | Immediate Consistency | Immediate Consistency | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | yes | no | no | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | tunable from ACID to Eventually Consistent | no | no | yes isolated transactions for atomic changes and binary logging for safe writes | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | Yes, tunable from durable to delayed durability to in-memory | yes | yes | yes The original contents of fields are not stored in the Manticore index. | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | Fine grained access rights according to SQL-standard with additional protections for files | fine grained access rights according to SQL-standard | no | no | fine grained access rights according to SQL-standard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Faircom DB formerly c-treeACE | HEAVY.AI Formerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022 | Hypertable | Manticore Search | 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 Monitoring PostgreSQL with Redgate Monitor FairCom kicks off new era of database technology USA - English provided by Google News Big Data Analytics: A Game Changer for Infrastructure HEAVY.AI Launches HEAVY 7.0, Introducing Real-Time Machine Learning Capabilities Making the most of geospatial intelligence OmniSci Gets HEAVY New Name and New CEO The insideBIGDATA IMPACT 50 List for Q4 2023 provided by Google News SQL and TimescaleDB. This article takes a closer look into… | by Alibaba Cloud TimescaleDB goes distributed; implements ‘Chunking’ over ‘Sharding’ for scaling-out Decorate your Windows XP with Hyperdesk The Collective: Customize Your Computer & Your Phone With Star Trek NoSQL Market: A well-defined technological growth map with an impact-analysis provided by Google News Integrating Manticore Search with Apache Superset Clickhouse vs Elasticsearch vs Manticore Search Query Times With a 1.7B NYC Taxi Rides Benchmark 8 Powerful Alternatives to Elasticsearch Manticore is a Faster Alternative to Elasticsearch in C++ Apex Legends hacker says game developers patched exploit used on streamers provided by Google News Let PostgreSQL Pick An Index For You Continuously replicate Amazon DynamoDB changes to Amazon Aurora PostgreSQL using AWS Lambda | Amazon ... Introducing OCI Database with PostgreSQL: Completing Our Cloud Database Suite for Every Need ServiceNow trades MariaDB for RaptorDB (PostgreSQL) General availability: Microsoft Entra ID integration with Azure Cosmos DB for PostgreSQL | Azure updates provided by Google News |
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