DBMS > Apache IoTDB vs. Datomic vs. Hive vs. PostgreSQL vs. Sphinx
System Properties Comparison Apache IoTDB vs. Datomic vs. Hive vs. PostgreSQL vs. Sphinx
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Name | Apache IoTDB Xexclude from comparison | Datomic Xexclude from comparison | Hive Xexclude from comparison | PostgreSQL Xexclude from comparison | Sphinx Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink | Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability | data warehouse software for querying and managing large distributed datasets, built on Hadoop | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | Open source search engine for searching in data from different sources, e.g. relational databases | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Time Series 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. | Search engine | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Document store Graph DBMS with Apache Age Spatial DBMS Vector DBMS with pgvector extension | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | iotdb.apache.org | www.datomic.com | hive.apache.org | www.postgresql.org | sphinxsearch.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html | docs.datomic.com | cwiki.apache.org/confluence/display/Hive/Home | www.postgresql.org/docs | sphinxsearch.com/docs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Apache Software Foundation | Cognitect | Apache Software Foundation initially developed by Facebook | PostgreSQL Global Development Group www.postgresql.org/developer | Sphinx Technologies Inc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2018 | 2012 | 2012 | 1989 1989: Postgres, 1996: PostgreSQL | 2001 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 1.1.0, April 2023 | 1.0.6735, June 2023 | 3.1.3, April 2022 | 16.3, May 2024 | 3.5.1, February 2023 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source Apache Version 2.0 | commercial limited edition free | Open Source Apache Version 2 | Open Source BSD | Open Source GPL version 2, commercial licence available | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Implementation language | Java | Java, Clojure | Java | C | C++ | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | All OS with a Java VM (>= 1.8) | All OS with a Java VM | All OS with a Java VM | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | FreeBSD Linux NetBSD OS X Solaris Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | yes | yes | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 | yes specific XML-type available, but no XML query functionality. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | yes | yes | yes | yes full-text index on all search fields | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | SQL-like query language | no | SQL-like DML and DDL statements | yes standard with numerous extensions | SQL-like query language (SphinxQL) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | JDBC Native API | RESTful HTTP API | JDBC ODBC Thrift | ADO.NET JDBC native C library ODBC streaming API for large objects | Proprietary protocol | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | C C# C++ Go Java Python Scala | Clojure Java | C++ Java PHP Python | .Net C C++ Delphi Java JDBC JavaScript (Node.js) Perl PHP Python Tcl | C++ unofficial client library Java Perl unofficial client library PHP Python Ruby unofficial client library | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | yes | yes Transaction Functions | yes user defined functions and integration of map-reduce | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes | By using transaction functions | no | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | horizontal partitioning (by time range) + vertical partitioning (by deviceId) | none But extensive use of caching in the application peers | Sharding | partitioning by range, list and (since PostgreSQL 11) by hash | Sharding Partitioning is done manually, search queries against distributed index is supported | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas | none But extensive use of caching in the application peers | selectable replication factor | Source-replica replication other methods possible by using 3rd party extensions | none | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | Integration with Hadoop and Spark | no | yes query execution via MapReduce | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency Strong Consistency with Raft | Immediate Consistency | Eventual Consistency | Immediate Consistency | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | no | no | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | no | ACID | no | ACID | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others) | yes | yes | yes The original contents of fields are not stored in the Sphinx index. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes | yes recommended only for testing and development | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | yes | no | Access rights for users, groups and roles | fine grained access rights according to SQL-standard | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Apache IoTDB | Datomic | Hive | PostgreSQL | Sphinx | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | Why is Hadoop not listed in the DB-Engines Ranking? | 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 | The DB-Engines ranking includes now search engines Monitoring PostgreSQL with Redgate Monitor TsFile: A Standard Format for IoT Time Series Data AMD EPYC 8324P / 8324PN Siena 32-Core Siena Linux Server Performance Review Apache Promotes IoT Database Project Benchmarking The Performance Impact To AMD Inception Mitigations IoTDB Provides Data Management for Industrial Edge IT provided by Google News Nubank buys firm behind Clojure programming language Zoona Case Study Architecting Software for Leverage TerminusDB Takes on Data Collaboration with a git-Like Approach Brazil’s Nubank acquires US software firm Cognitect, creator of Clojure and Datomic provided by Google News Apache Software Foundation Announces Apache® Hive 4.0 ASF Unveils the Next Evolution of Big Data Processing With the Launch of Hive 4.0 Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS | Amazon Web Services 18 Top Big Data Tools and Technologies to Know About in 2024 DataCentral: Uber's Observability and Chargeback Platform provided by Google News Deep PostgreSQL Thoughts: Valuing Currency At Build, Microsoft Fabric, PostgreSQL and Cosmos DB get AI enhancements Nutanix partners with EDB to fit database service for AI – Blocks and Files How to Import CSV Data Into PostgreSQL Using Spring Boot Batch Nutanix and EDB enhance PostgreSQL for enterprise apps provided by Google News Switching From Sphinx to MkDocs Documentation — What Did I Gain and Lose Manticore is a Faster Alternative to Elasticsearch in C++ Perplexity AI: From Its Use To Operation, Everything You Need To Know About Googles Newest Challenger The Pirate Bay was recently down for over a week due to a DDoS attack Beyond the Concert Hall: 5 Organizations Making a Difference in Classical Music in 2018 | WQXR Editorial provided by Google News |
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