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DBMS > Apache Spark (SQL) vs. RavenDB vs. Tarantool

System Properties Comparison Apache Spark (SQL) vs. RavenDB vs. Tarantool

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Editorial information provided by DB-Engines
NameApache Spark (SQL)  Xexclude from comparisonRavenDB  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionApache Spark SQL is a component on top of 'Spark Core' for structured data processingOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelRelational DBMSDocument storeDocument store
Key-value store
Relational DBMS
Secondary database modelsGraph DBMS
Spatial DBMS
Time Series DBMS
Spatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score20.40
Rank#29  Overall
#18  Relational DBMS
Score2.50
Rank#98  Overall
#17  Document stores
Score1.47
Rank#144  Overall
#25  Document stores
#24  Key-value stores
#66  Relational DBMS
Websitespark.apache.org/­sqlravendb.netwww.tarantool.io
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlravendb.net/­docswww.tarantool.io/­en/­doc
DeveloperApache Software FoundationHibernating RhinosVK
Initial release201420102008
Current release3.5.0 ( 2.13), September 20235.4, July 20222.10.0, May 2022
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoAGPL version 3, commercial license availableOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaC#C and C++
Server operating systemsLinux
OS X
Windows
Linux
macOS
Raspberry Pi
Windows
BSD
Linux
macOS
Data schemeyesschema-freeFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateyesnostring, 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.nono
Secondary indexesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query language (RQL)Full-featured ANSI SQL support
APIs and other access methodsJDBC
ODBC
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
Open binary protocol
Supported programming languagesJava
Python
R
Scala
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresnoyesLua, C and SQL stored procedures
Triggersnoyesyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CoreShardingSharding, 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 nodesnoneMulti-source replicationAsynchronous 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 methodsyes
Consistency concepts infoMethods to ensure consistency in a distributed systemDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.Casual 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 integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID, Cluster-wide transaction availableACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyes, cooperative multitasking
Durability infoSupport for making data persistentyesyesyes, write ahead logging
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 persistence
User concepts infoAccess controlnoAuthorization levels configured per client per databaseAccess 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
Apache Spark (SQL)RavenDBTarantool
DB-Engines blog posts

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

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