DBMS > Bangdb vs. IBM Db2 Event Store vs. InfluxDB vs. Microsoft SQL Server vs. PostgreSQL
System Properties Comparison Bangdb vs. IBM Db2 Event Store vs. InfluxDB vs. Microsoft SQL Server vs. PostgreSQL
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Name | Bangdb Xexclude from comparison | IBM Db2 Event Store Xexclude from comparison | InfluxDB Xexclude from comparison | Microsoft SQL Server Xexclude from comparison | PostgreSQL Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Converged and high performance database for device data, events, time series, document and graph | Distributed Event Store optimized for Internet of Things use cases | DBMS for storing time series, events and metrics | Microsofts flagship relational DBMS | 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 | Event Store Time Series DBMS | Time Series 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 | Spatial DBMS with GEO package | Document store Graph DBMS Spatial DBMS | Document store Graph DBMS with Apache Age Spatial DBMS Vector DBMS with pgvector extension | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | bangdb.com | www.ibm.com/products/db2-event-store | www.influxdata.com/products/influxdb-overview | www.microsoft.com/en-us/sql-server | www.postgresql.org | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | docs.bangdb.com | www.ibm.com/docs/en/db2-event-store | docs.influxdata.com/influxdb | learn.microsoft.com/en-US/sql/sql-server | www.postgresql.org/docs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Sachin Sinha, BangDB | IBM | Microsoft | PostgreSQL Global Development Group www.postgresql.org/developer | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2012 | 2017 | 2013 | 1989 | 1989 1989: Postgres, 1996: PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | BangDB 2.0, October 2021 | 2.0 | 2.7.6, April 2024 | SQL Server 2022, November 2022 | 16.3, May 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source BSD 3 | commercial free developer edition available | Open Source MIT-License; commercial enterprise version available | commercial restricted free version is available | 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++ | C and C++ | Go | C++ | C | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | Linux | Linux Linux, macOS, Windows for the developer addition | Linux OS X through Homebrew | Linux Windows | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | schema-free | yes | schema-free | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes: string, long, double, int, geospatial, stream, events | yes | Numeric data and Strings | 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 | no | no | yes | yes specific XML-type available, but no XML query functionality. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes secondary, composite, nested, reverse, geospatial | no | no | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | SQL like support with command line tool | yes through the embedded Spark runtime | SQL-like query language | yes | yes standard with numerous extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | Proprietary protocol RESTful HTTP API | ADO.NET DB2 Connect JDBC ODBC RESTful HTTP API | HTTP API JSON over UDP | ADO.NET JDBC ODBC OLE DB Tabular Data Stream (TDS) | ADO.NET JDBC native C library ODBC streaming API for large objects | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | C C# C++ Java Python | C C# C++ Cobol Delphi Fortran Go Java JavaScript (Node.js) Perl PHP Python R Ruby Scala Visual Basic | .Net Clojure Erlang Go Haskell Java JavaScript JavaScript (Node.js) Lisp Perl PHP Python R Ruby Rust Scala | C# C++ Delphi Go Java JavaScript (Node.js) PHP Python R Ruby Visual Basic | .Net C C++ Delphi Java JDBC JavaScript (Node.js) Perl PHP Python Tcl | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | no | yes | no | Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes, Notifications (with Streaming only) | no | no | yes | 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 | Sharding | Sharding in enterprise version only | tables can be distributed across several files (horizontal partitioning); sharding through federation | 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) | Active-active shard replication | selectable replication factor in enterprise version only | yes, but depending on the SQL-Server Edition | Source-replica replication other methods possible by using 3rd party extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Tunable consistency, set CAP knob accordingly | Eventual Consistency | Immediate Consistency | Immediate Consistency | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | no | no | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | no | no | ACID | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes, optimistic concurrency control | No - written data is immutable | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes, implements WAL (Write ahead log) as well | Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage | 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 | yes Depending on used storage engine | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | yes (enterprise version only) | fine grained access rights according to SQL-standard | simple rights management via user accounts | fine grained access rights according to SQL-standard | fine grained access rights according to SQL-standard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Bangdb | IBM Db2 Event Store | InfluxDB | Microsoft SQL Server | PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | InfluxData is the creator of InfluxDB , the open source time series database. It... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | Time to Value InfluxDB is available in all the popular languages and frameworks,... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | IoT & Sensor Monitoring Developers are witnessing the instrumentation of every available... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | InfluxData has more than 1,900 paying customers, including customers include MuleSoft,... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | Fastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | Open source core with closed source clustering available either on-premise or on... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
News | Monitoring Your Cloud Environments and Applications with InfluxDB Webinar Recap: Unleash the Full Potential of Your Time Series Data with InfluxDB and AWS Using Parquet’s Bloom Filters Efficiency Unleashed: Streamlining Workflows with the InfluxDB Management API What is DevRel at InfluxData | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Bangdb | IBM Db2 Event Store | InfluxDB | Microsoft SQL Server | PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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