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DBMS > Spark SQL vs. Tarantool vs. Transbase vs. Vertica vs. Yanza

System Properties Comparison Spark SQL vs. Tarantool vs. Transbase vs. Vertica vs. Yanza

Editorial information provided by DB-Engines
NameSpark SQL  Xexclude from comparisonTarantool  Xexclude from comparisonTransbase  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionSpark SQL is a component on top of 'Spark Core' for structured data processingIn-memory computing platform with a flexible data schema for efficiently building high-performance applicationsA resource-optimized, high-performance, universally applicable RDBMSCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.Time Series DBMS for IoT Applications
Primary database modelRelational DBMSDocument store
Key-value store
Relational DBMS
Relational DBMSRelational DBMS infoColumn orientedTime Series DBMS
Secondary database modelsSpatial DBMS infowith Tarantool/GIS extensionSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Score0.11
Rank#341  Overall
#150  Relational DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitespark.apache.org/­sqlwww.tarantool.iowww.transaction.de/­en/­products/­transbase.htmlwww.vertica.comyanza.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.tarantool.io/­en/­docwww.transaction.de/­en/­products/­transbase/­features.htmlvertica.com/­documentation
DeveloperApache Software FoundationVKTransaction Software GmbHOpenText infopreviously Micro Focus and Hewlett PackardYanza
Initial release20142008198720052015
Current release3.5.0 ( 2.13), September 20232.10.0, May 2022Transbase 8.3, 202212.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprisecommercial infofree development licensecommercial infoLimited community edition freecommercial infofree version available
Cloud-based only infoOnly available as a cloud servicenononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containersno infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageScalaC and C++C and C++C++
Server operating systemsLinux
OS X
Windows
BSD
Linux
macOS
FreeBSD
Linux
macOS
Solaris
Windows
LinuxWindows
Data schemeyesFlexible data schema: relational definition for tables with ability to store json-like documents in columnsyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.schema-free
Typing infopredefined data types such as float or dateyesstring, double, decimal, uuid, integer, blob, boolean, datetimeyesyesno
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.nonononono
Secondary indexesnoyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.no
SQL infoSupport of SQLSQL-like DML and DDL statementsFull-featured ANSI SQL supportyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.no
APIs and other access methodsJDBC
ODBC
Open binary protocolADO.NET
JDBC
ODBC
Proprietary native API
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
HTTP API
Supported programming languagesJava
Python
R
Scala
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
any language that supports HTTP calls
Server-side scripts infoStored proceduresnoLua, C and SQL stored proceduresyesyes, PostgreSQL PL/pgSQL, with minor differencesno
Triggersnoyes, before/after data modification events, on replication events, client session eventsyesyes, called Custom Alertsyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CoreSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.horizontal partitioning, hierarchical partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
Source-replica replicationMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono infoBi-directional Spark integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemCasual consistency across sharding partitions
Eventual consistency within replicaset partition infowhen using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition infowhen using Raft
Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactionsyesACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes, cooperative multitaskingyesyesyes
Durability infoSupport for making data persistentyesyes, write ahead loggingyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes, full featured in-memory storage engine with persistencenono
User concepts infoAccess controlnoAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles
fine grained access rights according to SQL-standardfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hashno
More information provided by the system vendor
Spark SQLTarantoolTransbaseVertica infoOpenText™ Vertica™Yanza
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more
Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
» more

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More resources
Spark SQLTarantoolTransbaseVertica infoOpenText™ Vertica™Yanza
DB-Engines blog posts

Data processing speed and reliability: in-memory synchronous replication
9 November 2021,  Vladimir Perepelytsya, Tarantool (sponsor) 

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