DBMS > Google Cloud Firestore vs. Microsoft Access vs. PostgreSQL vs. Quasardb vs. SingleStore
System Properties Comparison Google Cloud Firestore vs. Microsoft Access vs. PostgreSQL vs. Quasardb vs. SingleStore
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Name | Google Cloud Firestore Xexclude from comparison | Microsoft Access Xexclude from comparison | PostgreSQL Xexclude from comparison | Quasardb Xexclude from comparison | SingleStore former name was MemSQL Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products. | Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.) | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | Distributed, high-performance timeseries database | MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Document store | Relational DBMS | Relational DBMS with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module. | Time Series DBMS | Relational DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Document store Graph DBMS with Apache Age Spatial DBMS Vector DBMS with pgvector extension | Document store Spatial DBMS Time Series DBMS Vector DBMS | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | firebase.google.com/products/firestore | www.microsoft.com/en-us/microsoft-365/access | www.postgresql.org | quasar.ai | www.singlestore.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | firebase.google.com/docs/firestore | developer.microsoft.com/en-us/access | www.postgresql.org/docs | doc.quasar.ai/master | docs.singlestore.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Microsoft | PostgreSQL Global Development Group www.postgresql.org/developer | quasardb | SingleStore Inc. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2017 | 1992 | 1989 1989: Postgres, 1996: PostgreSQL | 2009 | 2013 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 1902 (16.0.11328.20222), March 2019 | 16.3, May 2024 | 3.14.1, January 2024 | 8.5, January 2024 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | commercial | commercial Bundled with Microsoft Office | Open Source BSD | commercial Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses | commercial free developer edition available | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | yes | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Implementation language | C++ | C | C++ | C++, Go | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | hosted | Windows Not a real database server, but making use of DLLs | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | BSD Linux OS X Windows | Linux 64 bit version required | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | schema-free | yes | yes | schema-free | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | yes | yes | yes integer and binary | 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. | no | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | yes | yes | yes with tags | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | no | yes but not compliant to any SQL standard | yes standard with numerous extensions | SQL-like query language | yes but no triggers and foreign keys | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | Android gRPC (using protocol buffers) API iOS JavaScript API RESTful HTTP API | ADO.NET DAO ODBC OLE DB | ADO.NET JDBC native C library ODBC streaming API for large objects | HTTP API | Cluster Management API as HTTP Rest and CLI HTTP API JDBC MongoDB API ODBC | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | Go Java JavaScript JavaScript (Node.js) Objective-C Python | C C# C++ Delphi Java (JDBC-ODBC) VBA Visual Basic.NET | .Net C C++ Delphi Java JDBC JavaScript (Node.js) Perl PHP Python Tcl | .Net C C# C++ Go Java JavaScript (Node.js) PHP Python R | Bash C C# Java JavaScript (Node.js) Python | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | yes, Firebase Rules & Cloud Functions | yes since Access 2010 using the ACE-engine | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes, with Cloud Functions | yes since Access 2010 using the ACE-engine | yes | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Sharding | none | partitioning by range, list and (since PostgreSQL 11) by hash | Sharding consistent hashing | Sharding hash partitioning | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | Multi-source replication | none | Source-replica replication other methods possible by using 3rd party extensions | Source-replica replication with selectable replication factor | Source-replica replication stores two copies of each physical data partition on two separate nodes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | Using Cloud Dataflow | no | no | with Hadoop integration | no can define user-defined aggregate functions for map-reduce-style calculations | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Immediate Consistency | Immediate Consistency | Immediate Consistency | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | yes | yes | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | yes | ACID but no files for transaction logging | ACID | ACID | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes, multi-version concurrency control (MVCC) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes but no files for transaction logging | yes | yes by using LevelDB | yes All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | no | yes Transient mode | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth. | no a simple user-level security was built in till version Access 2003 | fine grained access rights according to SQL-standard | Cryptographically strong user authentication and audit trail | Fine grained access control via users, groups and roles | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Google Cloud Firestore | Microsoft Access | PostgreSQL | Quasardb | SingleStore former name was MemSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | SingleStore offers a fully-managed , distributed, highly-scalable SQL database designed... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | SingleStore’s competitive advantages include: Easy and Simplified Architecture with... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | Driving Fast Analytics: SingleStore delivers the fastest and most scalable reporting... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | IEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | Customers in various industries worldwide including US and International Industry... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | F ree Tier and Enterprise Edition » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Google Cloud Firestore | Microsoft Access | PostgreSQL | Quasardb | SingleStore former name was MemSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | Cloud-based DBMS's popularity grows at high rates | MS Access drops in DB-Engines Ranking Microsoft SQL Server regained rank 2 in the DB-Engines popularity ranking New DB-Engines Ranking shows the popularity of database management systems | 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 | Turbocharge Your Application Development Using WebAssembly With SingleStoreDB Cloud-Based Analytics With SingleStoreDB SingleStore: The Increasing Momentum of Multi-Model Database Systems Realtime vs Cloud Firestore: Which Firebase Database to go? Google's AI-First Strategy Brings Vector Support To Cloud Databases Google's Cloud Firestore is now generally available Google launches Cloud Firestore, a new document database for app developers Google's Cloud-Native NoSQL Database Cloud Firestore Is Now Generally Available provided by Google News Abusing Microsoft Access "Linked Table" Feature to Perform NTLM Forced Authentication Attacks - Check Point Research Hackers Exploit Microsoft Access Feature to Steal Windows User’s NTLM Tokens After installing Navisworks, Office 2016 (32-bit) applications stopped launching MS access program to increase awareness and independence of those living with MS and disability How to Connect MS Access to MySQL via ODBC Driver provided by Google News Quasar Partners with PTC to Empower IoT Customers with High-Performance Data Solutions Record quasar is most luminous object in the universe QUASAR yacht (Bilgin, 46.8m, 2016) Quasar Selected by National Renewable Energy Laboratory to Help with Energy System De-risking and Optimization QuestDB gets $12M Series A funding amid growing interest in time-series databases provided by Google News Building a Modern Database: Nikita Shamgunov on Postgres and Beyond SingleStore CEO sees little future for purpose-built vector databases SingleStore Announces Real-time Data Platform to Further Accelerate AI, Analytics and Application Development SingleStore adds indexed vector search to Pro Max release for faster AI work – Blocks and Files SingleStore update adds new tools to fuel GenAI, analytics provided by Google News |
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