DBMS > EDB Postgres vs. Google Cloud Bigtable vs. Graphite vs. PostgreSQL vs. Splice Machine
System Properties Comparison EDB Postgres vs. Google Cloud Bigtable vs. Graphite vs. PostgreSQL vs. Splice Machine
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| Name | EDB Postgres Xexclude from comparison | Google Cloud Bigtable Xexclude from comparison | Graphite Xexclude from comparison | PostgreSQL Xexclude from comparison | Splice Machine Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Description | The EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration. | Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail. | Data logging and graphing tool for time series data  The storage layer (fixed size database) is called Whisper | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Primary database model | Relational DBMS | Key-value store Wide column store | 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 | Document store Spatial DBMS | Document store Graph DBMS with Apache AgeSpatial DBMS Vector DBMS with pgvector extension | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Website | www.enterprisedb.com | cloud.google.com/bigtable | github.com/graphite-project/graphite-web | www.postgresql.org | splicemachine.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | www.enterprisedb.com/docs | cloud.google.com/bigtable/docs | graphite.readthedocs.io | www.postgresql.org/docs | splicemachine.com/how-it-works | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Developer | EnterpriseDB | Chris Davis | PostgreSQL Global Development Group www.postgresql.org/developer | Splice Machine | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 2005 | 2015 | 2006 | 1989 1989: Postgres, 1996: PostgreSQL | 2014 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | 14, December 2021 | 16.2, February 2024 | 3.1, March 2021 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| License Commercial or Open Source | commercial BSD for PostgreSQL-components | commercial | Open Source Apache 2.0 | Open Source BSD | Open Source AGPL 3.0, commercial license available | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Cloud-based only Only available as a cloud service | no | yes | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed. | Aiven for PostgreSQL: Fully managed PostgreSQL for developers with 70+ extensions and flexible orchestration tools. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Implementation language | C | Python | C | Java | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server operating systems | Linux Windows | hosted | Linux Unix | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | Linux OS X Solaris Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Data scheme | yes | schema-free | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typing predefined data types such as float or date | yes | no | Numeric data only | 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. | yes specific XML-type available, but no XML query functionality. | no | no | yes specific XML-type available, but no XML query functionality. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary indexes | yes | no | no | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | yes standard with numerous extensions | no | no | yes standard with numerous extensions | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| APIs and other access methods | ADO.NET JDBC native C library ODBC streaming API for large objects | gRPC (using protocol buffers) API HappyBase (Python library) HBase compatible API (Java) | HTTP API Sockets | ADO.NET JDBC native C library ODBC streaming API for large objects | JDBC Native Spark Datasource ODBC | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Supported programming languages | .Net C C++ Delphi Java Perl PHP Python Tcl | C# C++ Go Java JavaScript (Node.js) Python | JavaScript (Node.js) Python | .Net C C++ Delphi Java JDBCJavaScript (Node.js) Perl PHP Python Tcl | C# C++ Java JavaScript (Node.js) Python R Scala | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server-side scripts Stored procedures | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | no | no | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | yes Java | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Triggers | yes | no | no | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Partitioning methods Methods for storing different data on different nodes | horizontal partitioning by hash, list or range | Sharding | none | partitioning by range, list and (since PostgreSQL 11) by hash | Shared Nothhing Auto-Sharding, Columnar Partitioning | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Replication methods Methods for redundantly storing data on multiple nodes | Multi-source replication | Internal replication in Colossus, and regional replication between two clusters in different zones | none | Source-replica replication other methods possible by using 3rd party extensions | Multi-source replication Source-replica replication | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| MapReduce Offers an API for user-defined Map/Reduce methods | no | yes | no | no | Yes, via Full Spark Integration | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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) | none | Immediate Consistency | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Foreign keys Referential integrity | yes | no | no | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | Atomic single-row operations | no | ACID | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Concurrency Support for concurrent manipulation of data | yes, multi-version concurrency control (MVCC) | yes | yes locking | yes | yes, multi-version concurrency control (MVCC) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Durability Support for making data persistent | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | no | no | no | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| User concepts Access control | fine grained access rights according to SQL-standard | Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM) | no | fine grained access rights according to SQL-standard | Access rights for users, groups and roles according to SQL-standard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 3rd parties | Timescale: Calling all PostgreSQL users – the 2023 State of PostgreSQL survey is now open! Share your favorite extensions, preferred frameworks, community experiences, and more. Take the survey today!
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| More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| EDB Postgres | Google Cloud Bigtable | Graphite | PostgreSQL | Splice Machine | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| DB-Engines blog posts | 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 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Conferences, events and webinars | Monitoring PostgreSQL with Redgate Monitor | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Recent citations in the news | EDB Puts Postgres in the Middle of Analytics Workflow with New Lakehouse Stack EDB Is Developing Its Flagship Database Into A Comprehensive Platform For Analytics, AI Key new features and innovations in EDB Postgres 16 EDB Closes the High Availability Gap for Postgres in the Cloud with EDB Postgres Distributed on BigAnimal EDB Introduces Two New Ways to Get Postgres in AWS Marketplace provided by Google News | Google's AI-First Strategy Brings Vector Support To Cloud Databases Google expands BigQuery with Gemini, brings vector support to cloud databases What is Google Bigtable? | Definition from TechTarget Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs Review: Google Bigtable scales with ease provided by Google News | The Billion Data Point Challenge: Building a Query Engine for High Cardinality Time Series Data Grafana Labs Announces Mimir Time Series Database Getting Started with Monitoring using Graphite How Grafana made observability accessible Grafana 4.0 Brings Major Enhancements to Leading Visualization Tool provided by Google News | Leveraging PostgreSQL for Cutting-Edge Generative AI Applications: Insights from Google's Product Managers Handle tables without primary keys while creating Amazon Aurora PostgreSQL zero-ETL integrations with Amazon ... Introducing OCI Database with PostgreSQL: Completing Our Cloud Database Suite for Every Need PostgreSQL or MySQL: What Should I Choose for My Full-Stack Project? PeerDB raises $3.6M to accelerate PostgreSQL data movement provided by Google News | Machine learning data pipeline outfit Splice Machine files for insolvency Splice Machine Launches the Splice Machine Feature Store to Simplify Feature Engineering and Democratize Machine ... Splice Machine Launches Feature Store to Simplify Feature Engineering Distributed SQL System Review: Snowflake vs Splice Machine Splice Machine Hadoop RDBMS Integrated with RedPoint Solution to Deliver Big Data Digital Marketing Platform provided by Google News | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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