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DBMS > Databricks vs. Google Cloud Datastore vs. Teradata vs. TerminusDB vs. VelocityDB

System Properties Comparison Databricks vs. Google Cloud Datastore vs. Teradata vs. TerminusDB vs. VelocityDB

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonTeradata  Xexclude from comparisonTerminusDB infoformer name was DataChemist  Xexclude from comparisonVelocityDB  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.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA hybrid cloud data analytics software platform (Teradata Vantage)Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationshipsA .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)
Primary database modelDocument store
Relational DBMS
Document storeRelational DBMSGraph DBMSGraph DBMS
Object oriented DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Time Series DBMS
Document store
RDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score45.33
Rank#21  Overall
#15  Relational DBMS
Score0.17
Rank#325  Overall
#29  Graph DBMS
Score0.05
Rank#358  Overall
#36  Graph DBMS
#16  Object oriented DBMS
Websitewww.databricks.comcloud.google.com/­datastorewww.teradata.comterminusdb.comvelocitydb.com
Technical documentationdocs.databricks.comcloud.google.com/­datastore/­docsdocs.teradata.comterminusdb.github.io/­terminusdb/­#velocitydb.com/­UserGuide
DeveloperDatabricksGoogleTeradataDataChemist Ltd.VelocityDB Inc
Initial release20132008198420182011
Current releaseTeradata Vantage 1.0 MU2, January 201911.0.0, January 20237.x
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoGPL V3commercial
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageProlog, RustC#
Server operating systemshostedhostedhosted
Linux
LinuxAny that supports .NET
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesyesyes
Typing infopredefined data types such as float or dateyes, details hereyesyesyes
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.yesnoyesnono
Secondary indexesyesyesyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash indexyes
SQL infoSupport of SQLwith Databricks SQLSQL-like query language (GQL)yes infoSQL 2016 + extensionsSQL-like query language (WOQL)no
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
OWL
RESTful HTTP API
WOQL (Web Object Query Language)
.Net
Supported programming languagesPython
R
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
JavaScript
Python
.Net
Server-side scripts infoStored proceduresuser defined functions and aggregatesusing Google App Engineyes infoUDFs, stored procedures, table functions in parallelyesno
TriggersCallbacks using the Google Apps EngineyesyesCallbacks are triggered when data changes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoHashingGraph PartitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication using PaxosMulti-source replication
Source-replica replication
Journaling Streams
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoin-memory journalingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardRole-based access controlBased on Windows Authentication
More information provided by the system vendor
DatabricksGoogle Cloud DatastoreTeradataTerminusDB infoformer name was DataChemistVelocityDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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