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DBMS > PouchDB vs. SingleStore vs. SurrealDB vs. TimescaleDB

System Properties Comparison PouchDB vs. SingleStore vs. SurrealDB vs. TimescaleDB

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Editorial information provided by DB-Engines
NamePouchDB  Xexclude from comparisonSingleStore infoformer name was MemSQL  Xexclude from comparisonSurrealDB  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionJavaScript DBMS with an API inspired by CouchDBMySQL 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 typeA fully ACID transactional, developer-friendly, multi-model DBMSA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelDocument storeRelational DBMSDocument store
Graph DBMS
Time Series DBMS
Secondary database modelsDocument store
Spatial DBMS
Time Series DBMS
Vector DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.28
Rank#115  Overall
#21  Document stores
Score5.60
Rank#62  Overall
#35  Relational DBMS
Score0.86
Rank#203  Overall
#34  Document stores
#18  Graph DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitepouchdb.comwww.singlestore.comsurrealdb.comwww.timescale.com
Technical documentationpouchdb.com/­guidesdocs.singlestore.comsurrealdb.com/­docsdocs.timescale.com
DeveloperApache Software FoundationSingleStore Inc.SurrealDB LtdTimescale
Initial release2012201320222017
Current release7.1.1, June 20198.5, January 2024v1.5.0, May 20242.15.0, May 2024
License infoCommercial or Open SourceOpen Sourcecommercial infofree developer edition availableOpen SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
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 languageJavaScriptC++, GoRustC
Server operating systemsserver-less, requires a JavaScript environment (browser, Node.js)Linux info64 bit version requiredLinux
macOS
Windows
Linux
OS X
Windows
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or datenoyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonoyes
Secondary indexesyes infovia viewsyesyes
SQL infoSupport of SQLnoyes infobut no triggers and foreign keysSQL-like query languageyes infofull PostgreSQL SQL syntax
APIs and other access methodsHTTP REST infoonly for PouchDB Server
JavaScript API
Cluster Management API infoas HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC
GraphQL
RESTful HTTP API
WebSocket
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesJavaScriptBash
C
C#
Java
JavaScript (Node.js)
Python
Deno
Go
JavaScript (Node.js)
Rust
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresView functions in JavaScriptyesuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyesnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infowith a proxy-based framework, named couchdb-loungeSharding infohash partitioningyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
Source-replica replication infostores two copies of each physical data partition on two separate nodesSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesno infocan define user-defined aggregate functions for map-reduce-style calculationsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyes infoby using IndexedDB, WebSQL or LevelDB as backendyes infoAll updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlnoFine grained access control via users, groups and rolesyes, based on authentication and database rulesfine grained access rights according to SQL-standard
More information provided by the system vendor
PouchDBSingleStore infoformer name was MemSQLSurrealDBTimescaleDB
Specific characteristicsSingleStore offers a fully-managed , distributed, highly-scalable SQL database designed...
» more
Competitive advantagesSingleStore’s competitive advantages include: Easy and Simplified Architecture with...
» more
Typical application scenariosDriving Fast Analytics: SingleStore delivers the fastest and most scalable reporting...
» more
Key customersIEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,...
» more
Market metricsCustomers in various industries worldwide including US and International Industry...
» more
Licensing and pricing modelsF ree Tier and Enterprise Edition
» more

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More resources
PouchDBSingleStore infoformer name was MemSQLSurrealDBTimescaleDB
DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

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17 October 2022,  Akmal Chaudhri, SingleStore (sponsor) 

Cloud-Based Analytics With SingleStoreDB
9 June 2022,  Akmal Chaudhri, SingleStore (sponsor) 

SingleStore: The Increasing Momentum of Multi-Model Database Systems
14 February 2022,  Akmal Chaudhri, SingleStore (sponsor) 

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Recent citations in the news

Building an Offline First App with PouchDB — SitePoint
10 March 2014, SitePoint

Getting Started with PouchDB Client-Side JavaScript Database — SitePoint
7 September 2016, SitePoint

3 Reasons To Think Offline First
22 March 2017, IBM

Create Offline Web Apps Using Service Workers & PouchDB — SitePoint
7 March 2017, SitePoint

Offline-first web and mobile apps: Top frameworks and components
22 January 2019, TechBeacon

provided by Google News

SingleStore CEO sees little future for purpose-built vector databases
24 January 2024, VentureBeat

SingleStore Announces Real-time Data Platform to Further Accelerate AI, Analytics and Application Development
24 January 2024, businesswire.com

Building a Modern Database: Nikita Shamgunov on Postgres and Beyond
18 April 2024, Madrona Venture Group

SingleStore adds indexed vector search to Pro Max release for faster AI work – Blocks and Files
29 January 2024, Blocks & Files

SingleStore CEO on High-Speed Database Currents
30 January 2024, Bloomberg

provided by Google News

SD Times Open-Source Project of the Week: SurrealDB
10 May 2024, SDTimes.com

Meet Tobie Morgan Hitchcock, CEO & Co-Founder Of SurrealDB
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Cloud, privacy and AI: Trends defining the future of data and databases
27 September 2023, Sifted

SurrealDB raises $6M for its database-as-a-service offering
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Introducing SurrealDB: A Quantum Leap in Database Technology
11 September 2023, TechRound

provided by Google News

TimescaleDB Is a Vector Database Now, Too
25 September 2023, Datanami

Timescale Acquires PopSQL to Bring a Modern, Collaborative SQL GUI to PostgreSQL Developers
4 April 2024, PR Newswire

Power IoT and time-series workloads with TimescaleDB for Azure Database for PostgreSQL
18 March 2019, Microsoft

Timescale Valuation Rockets to Over $1B with $110M Round, Marking the Explosive Rise of Time-Series Data
22 February 2022, Business Wire

TimescaleDB goes distributed; implements ‘Chunking’ over ‘Sharding’ for scaling-out
22 August 2019, Packt Hub

provided by Google News



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