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DBMS > Spark SQL vs. TimescaleDB vs. YottaDB vs. YugabyteDB

System Properties Comparison Spark SQL vs. TimescaleDB vs. YottaDB vs. YugabyteDB

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Editorial information provided by DB-Engines
NameSpark SQL  Xexclude from comparisonTimescaleDB  Xexclude from comparisonYottaDB  Xexclude from comparisonYugabyteDB  Xexclude from comparison
DescriptionSpark SQL is a component on top of 'Spark Core' for structured data processingA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLA fast and solid embedded Key-value storeHigh-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL.
Primary database modelRelational DBMSTime Series DBMSKey-value storeRelational DBMS
Secondary database modelsRelational DBMSRelational DBMS infousing the Octo pluginDocument store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Score0.28
Rank#306  Overall
#44  Key-value stores
Score2.63
Rank#109  Overall
#53  Relational DBMS
Websitespark.apache.org/­sqlwww.timescale.comyottadb.comwww.yugabyte.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.timescale.comyottadb.com/­resources/­documentationdocs.yugabyte.com
github.com/­yugabyte/­yugabyte-db
DeveloperApache Software FoundationTimescaleYottaDB, LLCYugabyte Inc.
Initial release2014201720012017
Current release3.5.0 ( 2.13), September 20232.15.0, May 20242.19, September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache 2.0Open Source infoAGPL 3.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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YugabyteDB Managed is the fully managed database-as-a-service offering of YugabyteDB. Get started quickly, and effortlessly ensure continuous availability and limitless scale of your cloud native applications.
Implementation languageScalaCCC and C++
Server operating systemsLinux
OS X
Windows
Linux
OS X
Windows
Docker
Linux
Linux
OS X
Data schemeyesyesschema-freedepending on used data model
Typing infopredefined data types such as float or dateyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data typesnoyes
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.noyesnono
Secondary indexesnoyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infofull PostgreSQL SQL syntaxby using the Octo pluginyes, PostgreSQL compatible
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
PostgreSQL wire protocol infousing the Octo plugin
Proprietary protocol
JDBC
YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language
YSQL - a fully relational SQL API that is wire compatible with the SQL language in PostgreSQL
Supported programming languagesJava
Python
R
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
Scala
Server-side scripts infoStored proceduresnouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellyes infosql, plpgsql, C
Triggersnoyesyes
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark Coreyes, across time and space (hash partitioning) attributesHash and Range Sharding, row-level geo-partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replication with hot standby and reads on replicas infoyesBased on Raft distributed consensus protocol, minimum 3 replicas for continuous availability
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyStrong consistency on writes and tunable consistency on reads
Foreign keys infoReferential integritynoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDoptimistic lockingDistributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture.
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyesyes infobased on RocksDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlnofine grained access rights according to SQL-standardUsers and groups based on OS-security mechanismsyes
More information provided by the system vendor
Spark SQLTimescaleDBYottaDBYugabyteDB
Specific characteristicsYugabyteDB is an open source distributed SQL database for cloud native transactional...
» more
Competitive advantagesPostgreSQL compatible: Get instantly productive with a PostgreSQL compatible RDBMS....
» more
Typical application scenariosSystems of record and engagement for cloud native applications that require resilience,...
» more
Market metrics2 Million+ lifetime clusters deployed, 6.5K+ GitHub stars, 7K YugabyteDB Community...
» more
Licensing and pricing modelsApache 2.0 license for the database
» more

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Spark SQLTimescaleDBYottaDBYugabyteDB
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