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DBMS > Databricks vs. Google Cloud Bigtable vs. Sadas Engine vs. Solr

System Properties Comparison Databricks vs. Google Cloud Bigtable vs. Sadas Engine vs. Solr

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonSadas Engine  Xexclude from comparisonSolr  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.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelDocument store
Relational DBMS
Key-value store
Wide column store
Relational DBMSSearch engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score0.07
Rank#373  Overall
#157  Relational DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Websitewww.databricks.comcloud.google.com/­bigtablewww.sadasengine.comsolr.apache.org
Technical documentationdocs.databricks.comcloud.google.com/­bigtable/­docswww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationsolr.apache.org/­resources.html
DeveloperDatabricksGoogleSADAS s.r.l.Apache Software Foundation
Initial release2013201520062006
Current release8.09.6.1, May 2024
License infoCommercial or Open Sourcecommercialcommercialcommercial infofree trial version availableOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java
Server operating systemshostedhostedAIX
Linux
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or datenoyesyes infosupports customizable data types and automatic typing
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.yesnonoyes
Secondary indexesyesnoyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLwith Databricks SQLnoyesSolr Parallel SQL Interface
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Proprietary protocol
Java API
RESTful HTTP/JSON API
Supported programming languagesPython
R
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
Groovy
Java
PHP
Python
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesnonoJava plugins
Triggersnonoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesInternal replication in Colossus, and regional replication between two clusters in different zonesnoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
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
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles according to SQL-standardyes
More information provided by the system vendor
DatabricksGoogle Cloud BigtableSadas EngineSolr
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksGoogle Cloud BigtableSadas EngineSolr
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