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DBMS > Brytlyt vs. EXASOL vs. Spark SQL vs. Tarantool

System Properties Comparison Brytlyt vs. EXASOL vs. Spark SQL vs. Tarantool

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Editorial information provided by DB-Engines
NameBrytlyt  Xexclude from comparisonEXASOL  Xexclude from comparisonSpark SQL  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Spark 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 applications
Primary database modelRelational DBMSRelational DBMSRelational DBMSDocument store
Key-value store
Relational DBMS
Secondary database modelsSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.29
Rank#288  Overall
#131  Relational DBMS
Score1.99
Rank#124  Overall
#58  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Websitebrytlyt.iowww.exasol.comspark.apache.org/­sqlwww.tarantool.io
Technical documentationdocs.brytlyt.iowww.exasol.com/­resourcesspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.tarantool.io/­en/­doc
DeveloperBrytlytExasolApache Software FoundationVK
Initial release2016200020142008
Current release5.0, August 20233.5.0 ( 2.13), September 20232.10.0, May 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
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.
Implementation languageC, C++ and CUDAScalaC and C++
Server operating systemsLinux
OS X
Windows
Linux
OS X
Windows
BSD
Linux
macOS
Data schemeyesyesyesFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateyesyesyesstring, double, decimal, uuid, integer, blob, boolean, datetime
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.yes infospecific XML-type available, but no XML query functionality.nonono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLyesyesSQL-like DML and DDL statementsFull-featured ANSI SQL support
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
.Net
JDBC
ODBC
WebSocket
JDBC
ODBC
Open binary protocol
Supported programming languages.Net
C
C++
Delphi
Java
Perl
Python
Tcl
Java
Lua
Python
R
Java
Python
R
Scala
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresuser defined functions infoin PL/pgSQLuser defined functionsnoLua, C and SQL stored procedures
Triggersyesyesnoyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark CoreSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoHadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyCasual 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
Foreign keys infoReferential integrityyesyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, cooperative multitasking
Durability infoSupport for making data persistentyesyesyesyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standardnoAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

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More resources
BrytlytEXASOLSpark SQLTarantool
DB-Engines blog posts

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

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Recent citations in the news

Brytlyt releases version 5.0, introducing a more intuitive, intelligent and flexible analytics platform
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