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DBMS > Databricks vs. Microsoft Azure AI Search vs. Sadas Engine vs. Tarantool

System Properties Comparison Databricks vs. Microsoft Azure AI Search vs. Sadas Engine vs. Tarantool

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonSadas Engine  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.Search-as-a-service for web and mobile app developmentSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelDocument store
Relational DBMS
Search engineRelational DBMSDocument store
Key-value store
Relational DBMS
Secondary database modelsVector DBMSSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score5.52
Rank#59  Overall
#6  Search engines
Score0.07
Rank#373  Overall
#157  Relational DBMS
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Websitewww.databricks.comazure.microsoft.com/­en-us/­services/­searchwww.sadasengine.comwww.tarantool.io
Technical documentationdocs.databricks.comlearn.microsoft.com/­en-us/­azure/­searchwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationwww.tarantool.io/­en/­doc
DeveloperDatabricksMicrosoftSADAS s.r.l.VK
Initial release2013201520062008
Current releaseV18.02.10.0, May 2022
License infoCommercial or Open Sourcecommercialcommercialcommercial infofree trial version availableOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C and C++
Server operating systemshostedhostedAIX
Linux
Windows
BSD
Linux
macOS
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateyesyesstring, 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.yesnonono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLwith Databricks SQLnoyesFull-featured ANSI SQL support
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
RESTful HTTP APIJDBC
ODBC
Proprietary protocol
Open binary protocol
Supported programming languagesPython
R
Scala
C#
Java
JavaScript
Python
.Net
C
C#
C++
Groovy
Java
PHP
Python
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresuser defined functions and aggregatesnonoLua, C and SQL stored procedures
Triggersnonoyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud servicehorizontal partitioningSharding, 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 nodesyesyes infoImplicit feature of the cloud servicenoneAsynchronous 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 methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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 integritynoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID, 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.nonoyes infomanaged by 'Learn by Usage'yes, full featured in-memory storage engine with persistence
User concepts infoAccess controlyes infousing Azure authenticationAccess rights for users, groups and roles according to SQL-standardAccess 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
DatabricksMicrosoft Azure AI SearchSadas EngineTarantool
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksMicrosoft Azure AI SearchSadas EngineTarantool
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