DBMS > Google Cloud Spanner vs. PostgreSQL vs. Sphinx vs. Splice Machine vs. Teradata Aster
System Properties Comparison Google Cloud Spanner vs. PostgreSQL vs. Sphinx vs. Splice Machine vs. Teradata Aster
| Editorial information provided by DB-Engines | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Name | Google Cloud Spanner Xexclude from comparison | PostgreSQL Xexclude from comparison | Sphinx Xexclude from comparison | Splice Machine Xexclude from comparison | Teradata Aster Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Description | A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play. | 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 | Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark | Platform for big data analytics on multistructured data sources and types | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Primary database model | 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 | Relational DBMS | Relational DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary database models | Document store Graph DBMS with Apache AgeSpatial DBMS Vector DBMS with pgvector extension | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Website | cloud.google.com/spanner | www.postgresql.org | sphinxsearch.com | splicemachine.com | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | cloud.google.com/spanner/docs | www.postgresql.org/docs | sphinxsearch.com/docs | splicemachine.com/how-it-works | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Developer | PostgreSQL Global Development Group www.postgresql.org/developer | Sphinx Technologies Inc. | Splice Machine | Teradata | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 2017 | 1989 1989: Postgres, 1996: PostgreSQL | 2001 | 2014 | 2005 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | 16.3, May 2024 | 3.5.1, February 2023 | 3.1, March 2021 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| License Commercial or Open Source | commercial | Open Source BSD | Open Source GPL version 2, commercial licence available | Open Source AGPL 3.0, commercial license available | commercial | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Cloud-based only Only available as a cloud service | yes | no | 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 | C++ | Java | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server operating systems | hosted | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | FreeBSD Linux NetBSD OS X Solaris Windows | Linux OS X Solaris Windows | Linux | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Data scheme | yes | yes | yes | yes | Flexible Schema (defined schema, partial schema, schema free) defined schema within the relational store; partial schema or schema free in the Aster File Store | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typing predefined data types such as float or date | yes | yes | no | 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 | yes specific XML-type available, but no XML query functionality. | yes in Aster File Store | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary indexes | yes | yes | yes full-text index on all search fields | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | yes Query statements complying to ANSI 2011 | yes standard with numerous extensions | SQL-like query language (SphinxQL) | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| APIs and other access methods | gRPC (using protocol buffers) API JDBC At present, JDBC supports read-only queries. No support for DDL or DML statements.RESTful HTTP API | ADO.NET JDBC native C library ODBC streaming API for large objects | Proprietary protocol | JDBC Native Spark Datasource ODBC | ADO.NET JDBC ODBC OLE DB | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Supported programming languages | Go Java JavaScript (Node.js) Python | .Net C C++ Delphi Java JDBCJavaScript (Node.js) Perl PHP Python Tcl | C++ unofficial client library Java Perl unofficial client libraryPHP Python Ruby unofficial client library | C# C++ Java JavaScript (Node.js) Python R Scala | C C# C++ Java Python R | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server-side scripts Stored procedures | no | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | no | yes Java | R packages | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Triggers | no | yes | no | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Partitioning methods Methods for storing different data on different nodes | Sharding | partitioning by range, list and (since PostgreSQL 11) by hash | Sharding Partitioning is done manually, search queries against distributed index is supported | Shared Nothhing Auto-Sharding, Columnar Partitioning | Sharding | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Replication methods Methods for redundantly storing data on multiple nodes | Multi-source replication with 3 replicas for regional instances. | Source-replica replication other methods possible by using 3rd party extensions | none | Multi-source replication Source-replica replication | yes Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| MapReduce Offers an API for user-defined Map/Reduce methods | yes using Google Cloud Dataflow | no | no | Yes, via Full Spark Integration | yes SQL Map-Reduce Framework | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Immediate Consistency | Immediate Consistency | Immediate Consistency or Eventual Consistency depending on configuration | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Foreign keys Referential integrity | yes by using interleaved tables, this features focuses more on performance improvements than on referential integrity | yes | no | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID Strict serializable isolation | ACID | no | ACID | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes, multi-version concurrency control (MVCC) | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Durability Support for making data persistent | yes | yes | yes The original contents of fields are not stored in the Sphinx index. | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | no | no | yes | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| User concepts Access control | Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM) | fine grained access rights according to SQL-standard | no | Access rights for users, groups and roles according to SQL-standard | fine grained access rights according to SQL-standard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendorWe invite representatives of system vendors to contact us for updating and extending the system information, | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Google Cloud Spanner | PostgreSQL | Sphinx | Splice Machine | Teradata Aster | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 | The DB-Engines ranking includes now search engines | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Conferences, events and webinars | Monitoring PostgreSQL with Redgate Monitor | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Recent citations in the news | Google Improves Cloud Spanner: More Compute and Storage without Price Increase Google turns up the heat on AWS, claims Cloud Spanner is half the cost of DynamoDB Google makes its Cloud Spanner database service faster and more cost-efficient Google Spanner: When Do You Need to Move to It? More AI Added to Google Cloud's Databases provided by Google News | ServiceNow trades MariaDB for RaptorDB (PostgreSQL) AGEDB Technology Launches PGTS - PostgreSQL Tech-Support First Principles: Optimizing PostgreSQL for the cloud Automatically Generate Types for Your PostgreSQL Database General availability: Microsoft Entra ID integration with Azure Cosmos DB for PostgreSQL | Azure updates 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 How to Build 600+ Links in One Month Beyond the Concert Hall: 5 Organizations Making a Difference in Classical Music in 2018 | WQXR Editorial 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 ... How Splice Machine's Data Platform for Intelligent Apps Works Splice Machine Launches Feature Store to Simplify Feature Engineering Distributed SQL System Review: Snowflake vs Splice Machine provided by Google News | Northwestern Analytics Partners with Teradata Aster to Host Hackathon Teradata Aster gets graph database, HDFS-compatible file store Teradata Provides the Simplest Way to Bring the Science of Data to the Art of Business Teradata's Aster shows how the flowers of fraud bloom Case study: Siemens reduces train failures with Teradata Aster provided by Google News | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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