DBMS > DuckDB vs. Google Cloud Bigtable vs. HarperDB vs. PostgreSQL vs. Solr
System Properties Comparison DuckDB vs. Google Cloud Bigtable vs. HarperDB vs. PostgreSQL vs. Solr
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| Name | DuckDB Xexclude from comparison | Google Cloud Bigtable Xexclude from comparison | HarperDB Xexclude from comparison | PostgreSQL Xexclude from comparison | Solr Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Description | An embeddable, in-process, column-oriented SQL OLAP RDBMS | Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail. | Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture. | Widely used open source RDBMS  Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | A widely used distributed, scalable search engine based on Apache Lucene | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Primary database model | Relational DBMS | Key-value store Wide column store | Document store | 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 AgeSpatial DBMS Vector DBMS with pgvector extension | Spatial DBMS | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Website | duckdb.org | cloud.google.com/bigtable | www.harperdb.io | www.postgresql.org | solr.apache.org | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | duckdb.org/docs | cloud.google.com/bigtable/docs | docs.harperdb.io/docs | www.postgresql.org/docs | solr.apache.org/resources.html | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Developer | HarperDB | PostgreSQL Global Development Group www.postgresql.org/developer | Apache Software Foundation | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 2018 | 2015 | 2017 | 1989 1989: Postgres, 1996: PostgreSQL | 2006 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | 1.0.0, June 2024 | 3.1, August 2021 | 16.3, May 2024 | 9.6.1, May 2024 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| License Commercial or Open Source | Open Source MIT License | commercial | commercial free community edition available | Open Source BSD | Open Source Apache Version 2 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Cloud-based only Only available as a cloud service | no | yes | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Implementation language | C++ | Node.js | C | Java | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server operating systems | server-less | hosted | Linux OS X | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | All OS with a Java VM runs as a servlet in servlet container (e.g. Tomcat, Jetty is included) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Data scheme | yes | schema-free | dynamic schema | yes | yes Dynamic Fields enables on-the-fly addition of new fields | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typing predefined data types such as float or date | yes | no | yes JSON data types | yes | yes supports customizable data types and automatic typing | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 specific XML-type available, but no XML query functionality. | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary indexes | yes | no | yes | yes | yes All search fields are automatically indexed | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | yes | no | SQL-like data manipulation statements | yes standard with numerous extensions | Solr Parallel SQL Interface | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| APIs and other access methods | Arrow Database Connectivity (ADBC) CLI Client JDBC ODBC | gRPC (using protocol buffers) API HappyBase (Python library) HBase compatible API (Java) | JDBC ODBC React Hooks RESTful HTTP/JSON API WebSocket | ADO.NET JDBC native C library ODBC streaming API for large objects | Java API RESTful HTTP/JSON API | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Supported programming languages | C C# 3rd party driverC++ Crystal 3rd party driverGo 3rd party driverJava Lisp 3rd party driverPython R Ruby 3rd party driverRust Swift Zig 3rd party driver | C# C++ Go Java JavaScript (Node.js) Python | .Net C C# C++ ColdFusion D Dart Delphi Erlang Go Haskell Java JavaScript (Node.js) Lisp MatLab Objective C Perl PHP PowerShell Prolog Python R Ruby Rust Scala Swift | .Net C C++ Delphi Java JDBCJavaScript (Node.js) Perl PHP Python Tcl | .Net Erlang Java JavaScript any language that supports sockets and either XML or JSON Perl PHP Python Ruby Scala | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server-side scripts Stored procedures | no | no | Custom Functions since release 3.1 | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | Java plugins | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Triggers | no | no | no | yes | yes User configurable commands triggered on index changes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Partitioning methods Methods for storing different data on different nodes | none | Sharding | A table resides as a whole on one (or more) nodes in a cluster | partitioning by range, list and (since PostgreSQL 11) by hash | Sharding | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Replication methods Methods for redundantly storing data on multiple nodes | none | Internal replication in Colossus, and regional replication between two clusters in different zones | yes the nodes on which a table resides can be defined | Source-replica replication other methods possible by using 3rd party extensions | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| MapReduce Offers an API for user-defined Map/Reduce methods | no | yes | no | no | spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters) | Immediate Consistency | Immediate Consistency | Eventual Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Foreign keys Referential integrity | no | no | no | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | Atomic single-row operations | Atomic execution of specific operations | ACID | optimistic locking | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Concurrency Support for concurrent manipulation of data | yes, multi-version concurrency control (MVCC) | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Durability Support for making data persistent | yes | yes | yes, using LMDB | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes | no | yes | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| User concepts Access control | no | Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM) | Access rights for users and roles | fine grained access rights according to SQL-standard | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| DuckDB | Google Cloud Bigtable | HarperDB | PostgreSQL | Solr | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 | Elasticsearch replaced Solr as the most popular search engine Enterprise Search Engines almost double their popularity in the last 12 months The DB-Engines ranking includes now search engines MotherDuck Announces General Availability; Brings Simplicity and Power of DuckDB in a Serverless Data Warehouse DuckDB: The tiny but powerful analytics database DuckDB promises greater stability with 1.0 release My First Billion (of Rows) in DuckDB | by João Pedro | May, 2024 DuckDB: In-Process Python Analytics for Not-Quite-Big Data provided by Google News Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs Google scales up Cloud Bigtable NoSQL database Review: Google Bigtable scales with ease Google Cloud makes it cheaper to run smaller workloads on Bigtable Google introduces Cloud Bigtable managed NoSQL database to process data at scale provided by Google News Serent Capital invests in software firm HarperDB HarperDB Attracts Significant Growth Investment from Serent Capital HarperDB Receives Growth Investment from Serent Capital Startups of the Year 2023: Meet HarperDB - A Database and Application Development Platform Jaxon Repp on HarperDB Distributed Database Platform provided by Google News PostgreSQL is Now Faster than Pinecone, 75% Cheaper, with New Open Source Extensions Timescale unveils high-performance AI vector database extensions for PostgreSQL PostgreSQL Tutorial: Definition, Commands, & Features Raise the bar on AI-powered app development with Azure Database for PostgreSQL How to implement a better like, views, comment counters in PostgreSQL? provided by Google News SOLR-led walkout demands better conditions for Compass workers Solr Network Launches Groundbreaking Solana Token Creator (SOLR) Technical Data SOLR hosts teach-in of labor movements at Northwestern Top 5 stock gainers and losers: SOLR.V, GRSL.V, ANON.C provided by Google News | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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