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DBMS > Databricks vs. Fauna vs. Google Cloud Bigtable vs. Quasardb vs. TimesTen

System Properties Comparison Databricks vs. Fauna vs. Google Cloud Bigtable vs. Quasardb vs. TimesTen

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonFauna infopreviously named FaunaDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonQuasardb  Xexclude from comparisonTimesTen  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.Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Distributed, high-performance timeseries databaseIn-Memory RDBMS compatible to Oracle
Primary database modelDocument store
Relational DBMS
Document store
Graph DBMS
Relational DBMS
Time Series DBMS
Key-value store
Wide column store
Time Series DBMSRelational 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
Score1.52
Rank#153  Overall
#26  Document stores
#14  Graph DBMS
#71  Relational DBMS
#13  Time Series DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score1.31
Rank#163  Overall
#74  Relational DBMS
Websitewww.databricks.comfauna.comcloud.google.com/­bigtablequasar.aiwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationdocs.databricks.comdocs.fauna.comcloud.google.com/­bigtable/­docsdoc.quasar.ai/­masterdocs.oracle.com/­database/­timesten-18.1
DeveloperDatabricksFauna, Inc.GooglequasardbOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release20132014201520091998
Current release3.14.1, January 202411 Release 2 (11.2.2.8.0)
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensescommercial
Cloud-based only infoOnly available as a cloud serviceyesyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageScalaC++
Server operating systemshostedhostedhostedBSD
Linux
OS X
Windows
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or datenonoyes infointeger and binaryyes
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.yesnononono
Secondary indexesyesyesnoyes infowith tagsyes
SQL infoSupport of SQLwith Databricks SQLnonoSQL-like query languageyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
RESTful HTTP APIgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP APIJDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languagesPython
R
Scala
C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresuser defined functions and aggregatesuser defined functionsnonoPL/SQL
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning infoconsistent hashingShardingSharding infoconsistent hashingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replicationInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replication with selectable replication factorMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyeswith Hadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDAtomic single-row operationsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby using LevelDByes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes infoTransient modeyes
User concepts infoAccess controlIdentity management, authentication, and access controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Cryptographically strong user authentication and audit trailfine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksFauna infopreviously named FaunaDBGoogle Cloud BigtableQuasardbTimesTen
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksFauna infopreviously named FaunaDBGoogle Cloud BigtableQuasardbTimesTen
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