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DBMS > Databricks vs. HBase vs. Tarantool

System Properties Comparison Databricks vs. HBase vs. Tarantool

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonHBase  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Wide-column store based on Apache Hadoop and on concepts of BigTableIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelDocument store
Relational DBMS
Wide column storeDocument 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
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Websitewww.databricks.comhbase.apache.orgwww.tarantool.io
Technical documentationdocs.databricks.comhbase.apache.org/­book.htmlwww.tarantool.io/­en/­doc
DeveloperDatabricksApache Software Foundation infoApache top-level project, originally developed by PowersetVK
Initial release201320082008
Current release2.3.4, January 20212.10.0, May 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2Open Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++
Server operating systemshostedLinux
Unix
Windows infousing Cygwin
BSD
Linux
macOS
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-free, schema definition possibleFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateoptions to bring your own types, AVROstring, 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.yesnono
Secondary indexesyesnoyes
SQL infoSupport of SQLwith Databricks SQLnoFull-featured ANSI SQL support
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP API
Thrift
Open binary protocol
Supported programming languagesPython
R
Scala
C
C#
C++
Groovy
Java
PHP
Python
Scala
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infoCoprocessors in JavaLua, C and SQL stored procedures
Triggersyesyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesShardingSharding, 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 nodesyesMulti-source replication
Source-replica replication
Asynchronous 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 systemImmediate ConsistencyImmediate Consistency or Eventual 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 integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDSingle row ACID (across millions of columns)ACID, 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.noyesyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles
More information provided by the system vendor
DatabricksHBaseTarantool
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksHBaseTarantool
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