DBMS > GigaSpaces vs. IBM Db2 Event Store vs. InfluxDB vs. PostgreSQL vs. YugabyteDB
System Properties Comparison GigaSpaces vs. IBM Db2 Event Store vs. InfluxDB vs. PostgreSQL vs. YugabyteDB
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| Name | GigaSpaces Xexclude from comparison | IBM Db2 Event Store Xexclude from comparison | InfluxDB Xexclude from comparison | PostgreSQL Xexclude from comparison | YugabyteDB Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Description | High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions | Distributed Event Store optimized for Internet of Things use cases | DBMS for storing time series, events and metrics | Widely used open source RDBMS  Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | High-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Primary database model | Document store Object oriented DBMS Values are user defined objects | Event Store Time Series DBMS | Time Series DBMS | Relational DBMS with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module. | Relational DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary database models | Graph DBMS Search engine | Spatial DBMS with GEO package | Document store Graph DBMS with Apache AgeSpatial DBMS Vector DBMS with pgvector extension | Document store Wide column store | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Website | www.gigaspaces.com | www.ibm.com/products/db2-event-store | www.influxdata.com/products/influxdb-overview | www.postgresql.org | www.yugabyte.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | docs.gigaspaces.com/latest/landing.html | www.ibm.com/docs/en/db2-event-store | docs.influxdata.com/influxdb | www.postgresql.org/docs | docs.yugabyte.com github.com/yugabyte/yugabyte-db | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Developer | Gigaspaces Technologies | IBM | PostgreSQL Global Development Group www.postgresql.org/developer | Yugabyte Inc. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 2000 | 2017 | 2013 | 1989 1989: Postgres, 1996: PostgreSQL | 2017 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | 15.5, September 2020 | 2.0 | 2.7.6, April 2024 | 16.3, May 2024 | 2.19, September 2023 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| License Commercial or Open Source | Open Source Apache Version 2; Commercial licenses available | commercial free developer edition available | Open Source MIT-License; commercial enterprise version available | Open Source BSD | Open Source Apache 2.0 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Cloud-based only Only available as a cloud service | no | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| YugabyteDB Managed is the fully managed database-as-a-service offering of YugabyteDB. Get started quickly, and effortlessly ensure continuous availability and limitless scale of your cloud native applications. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Implementation language | Java, C++, .Net | C and C++ | Go | C | C and C++ | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server operating systems | Linux macOS Solaris Windows | Linux Linux, macOS, Windows for the developer addition | Linux OS X through Homebrew | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | Linux OS X | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Data scheme | schema-free | yes | schema-free | yes | depending on used data model | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typing predefined data types such as float or date | yes | 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 XML can be used for describing objects metadata | no | no | yes specific XML-type available, but no XML query functionality. | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary indexes | yes | no | no | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | SQL-99 for query and DML statements | yes through the embedded Spark runtime | SQL-like query language | yes standard with numerous extensions | yes, PostgreSQL compatible | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| APIs and other access methods | GigaSpaces LRMI Hibernate JCache JDBC JPA ODBC RESTful HTTP API Spring Data | ADO.NET DB2 Connect JDBC ODBC RESTful HTTP API | HTTP API JSON over UDP | ADO.NET JDBC native C library ODBC streaming API for large objects | JDBC YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language YSQL - a fully relational SQL API that is wire compatible with the SQL language in PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Supported programming languages | .Net C++ Java Python Scala | 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 | .Net C C++ Delphi Java JDBCJavaScript (Node.js) Perl PHP Python Tcl | C C# C++ Go Java JavaScript (Node.js) PHP Python Ruby Rust Scala | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server-side scripts Stored procedures | yes | yes | no | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | yes sql, plpgsql, C | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Triggers | yes, event driven architecture | no | no | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Partitioning methods Methods for storing different data on different nodes | Sharding | Sharding | Sharding in enterprise version only | partitioning by range, list and (since PostgreSQL 11) by hash | Hash and Range Sharding, row-level geo-partitioning | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Replication methods Methods for redundantly storing data on multiple nodes | Multi-source replication synchronous or asynchronous Source-replica replication synchronous or asynchronous | Active-active shard replication | selectable replication factor in enterprise version only | Source-replica replication other methods possible by using 3rd party extensions | Based on Raft distributed consensus protocol, minimum 3 replicas for continuous availability | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| MapReduce Offers an API for user-defined Map/Reduce methods | yes Map-Reduce pattern can be built with XAP task executors | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency Consistency level configurable: ALL, QUORUM, ANY | Eventual Consistency | Immediate Consistency | Strong consistency on writes and tunable consistency on reads | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 | Distributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Concurrency Support for concurrent manipulation of data | yes | No - written data is immutable | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Durability Support for making data persistent | yes | Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage | yes | yes | yes based on RocksDB | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes | yes | yes Depending on used storage engine | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| User concepts Access control | Role-based access control | fine grained access rights according to SQL-standard | simple rights management via user accounts | fine grained access rights according to SQL-standard | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| GigaSpaces | IBM Db2 Event Store | InfluxDB | PostgreSQL | YugabyteDB | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Specific characteristics | InfluxData is the creator of InfluxDB , the open source time series database. It... » more | YugabyteDB is an open source distributed SQL database for cloud native transactional... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Competitive advantages | Time to Value InfluxDB is available in all the popular languages and frameworks,... » more | PostgreSQL compatible: Get instantly productive with a PostgreSQL compatible RDBMS.... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typical application scenarios | IoT & Sensor Monitoring Developers are witnessing the instrumentation of every available... » more | Systems of record and engagement for cloud native applications that require resilience,... » 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 | 2 Million+ lifetime clusters deployed, 6.5K+ GitHub stars, 7K YugabyteDB Community... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Licensing and pricing models | Open source core with closed source clustering available either on-premise or on... » more | Apache 2.0 license for the database » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| News | An Introductory Guide to Grafana Alerts What to Expect When You’re Expecting InfluxDB: A Guide Introduction to Apache Iceberg Converting Timestamp to Date in Java A Detailed Guide to C# TimeSpan | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| GigaSpaces | IBM Db2 Event Store | InfluxDB | PostgreSQL | YugabyteDB | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| DB-Engines blog posts | Why Build a Time Series Data Platform? Time Series DBMS are the database category with the fastest increase in popularity Time Series DBMS as a new trend? | 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 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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