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DBMS > Databricks vs. eXtremeDB vs. Google Cloud Spanner vs. TigerGraph

System Properties Comparison Databricks vs. eXtremeDB vs. Google Cloud Spanner vs. TigerGraph

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisoneXtremeDB  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonTigerGraph  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.Natively in-memory DBMS with options for persistency, high-availability and clusteringA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelDocument store
Relational DBMS
Relational DBMS
Time Series DBMS
Relational DBMSGraph 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
Score0.74
Rank#223  Overall
#103  Relational DBMS
#18  Time Series DBMS
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score1.83
Rank#139  Overall
#13  Graph DBMS
Websitewww.databricks.comwww.mcobject.comcloud.google.com/­spannerwww.tigergraph.com
Technical documentationdocs.databricks.comwww.mcobject.com/­docs/­extremedb.htmcloud.google.com/­spanner/­docsdocs.tigergraph.com
DeveloperDatabricksMcObjectGoogle
Initial release2013200120172017
Current release8.2, 2021
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++C++
Server operating systemshostedAIX
HP-UX
Linux
macOS
Solaris
Windows
hostedLinux
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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.yesno infosupport of XML interfaces availablenono
Secondary indexesyesyesyes
SQL infoSupport of SQLwith Databricks SQLyes infowith the option: eXtremeSQLyes infoQuery statements complying to ANSI 2011SQL-like query language (GSQL)
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languagesPython
R
Scala
.Net
C
C#
C++
Java
Lua
Python
Scala
Go
Java
JavaScript (Node.js)
Python
C++
Java
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesnoyes
Triggersyes infoby defining eventsnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning / shardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesActive Replication Fabricâ„¢ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
Multi-source replication with 3 replicas for regional instances.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoStrict serializable isolationACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyesyes
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.noyesnono
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access control
More information provided by the system vendor
DatabrickseXtremeDBGoogle Cloud SpannerTigerGraph
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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eXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
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Competitive advantageseXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
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Typical application scenariosIoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
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Key customersSchneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more
Market metricsWith hundreds of customers and over 30 million devices/applications using the product...
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Licensing and pricing modelsFor server use cases, there is a simple per-server license irrespective of the number...
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DatabrickseXtremeDBGoogle Cloud SpannerTigerGraph
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