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DBMS > Databricks vs. Google Cloud Bigtable vs. Solr vs. TypeDB

System Properties Comparison Databricks vs. Google Cloud Bigtable vs. Solr vs. TypeDB

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonSolr  Xexclude from comparisonTypeDB infoformerly named Grakn  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.A widely used distributed, scalable search engine based on Apache LuceneTypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language
Primary database modelDocument store
Relational DBMS
Key-value store
Wide column store
Search engineGraph DBMS
Relational DBMS infoOften described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score42.91
Rank#24  Overall
#3  Search engines
Score0.65
Rank#234  Overall
#20  Graph DBMS
#107  Relational DBMS
Websitewww.databricks.comcloud.google.com/­bigtablesolr.apache.orgtypedb.com
Technical documentationdocs.databricks.comcloud.google.com/­bigtable/­docssolr.apache.org/­resources.htmltypedb.com/­docs
DeveloperDatabricksGoogleApache Software FoundationVaticle
Initial release2013201520062016
Current release9.6.0, April 20242.26.3, January 2024
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2Open Source infoGPL Version 3, commercial licenses available
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava
Server operating systemshostedhostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or datenoyes infosupports customizable data types and automatic typingyes
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.yesnoyesno
Secondary indexesyesnoyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLwith Databricks SQLnoSolr Parallel SQL Interfaceno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Java API
RESTful HTTP/JSON API
gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)
Supported programming languagesPython
R
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoJava pluginsno
Triggersnoyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoby using Cassandra
Replication methods infoMethods for redundantly storing data on multiple nodesyesInternal replication in Colossus, and regional replication between two clusters in different zonesyesMulti-source replication infoby using Cassandra
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceyes infoby using Apache Kafka and Apache Zookeeper
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono infosubstituted by the relationship feature
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsoptimistic lockingACID
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.nonoyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yesyes infoat REST API level; other APIs in progress
More information provided by the system vendor
DatabricksGoogle Cloud BigtableSolrTypeDB infoformerly named Grakn
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
TypeDB is a polymorphic database with a conceptual data model, a strong subtyping...
» more
Competitive advantagesTypeDB provides a new level of expressivity, extensibility, interoperability, and...
» more
Typical application scenariosLife sciences : TypeDB makes working with biological data much easier and accelerates...
» more
Licensing and pricing modelsApache f or language drivers, and AGPL and Commercial for the database server. The...
» more

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DatabricksGoogle Cloud BigtableSolrTypeDB infoformerly named Grakn
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