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DBMS > Databricks vs. Qdrant vs. TigerGraph vs. TinkerGraph

System Properties Comparison Databricks vs. Qdrant vs. TigerGraph vs. TinkerGraph

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonQdrant  Xexclude from comparisonTigerGraph  Xexclude from comparisonTinkerGraph  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.A high-performance vector database with neural network or semantic-based matchingA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-timeA lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API
Primary database modelDocument store
Relational DBMS
Vector DBMSGraph DBMSGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score84.24
Rank#14  Overall
#2  Document stores
#9  Relational DBMS
Score1.53
Rank#145  Overall
#7  Vector DBMS
Score1.44
Rank#152  Overall
#14  Graph DBMS
Score0.08
Rank#345  Overall
#34  Graph DBMS
Websitewww.databricks.comgithub.com/­qdrant/­qdrant
qdrant.tech
www.tigergraph.comtinkerpop.apache.org/­docs/­current/­reference/­#tinkergraph-gremlin
Technical documentationdocs.databricks.comqdrant.tech/­documentationdocs.tigergraph.com
DeveloperDatabricksQdrant
Initial release2013202120172009
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageRustC++Java
Server operating systemshostedDocker
Linux
macOS
Windows
Linux
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesschema-free
Typing infopredefined data types such as float or dateNumbers, Strings, Geo, Booleanyesyes
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.yesnonono
Secondary indexesyesyes infoKeywords, numberic ranges, geo, full-textno
SQL infoSupport of SQLwith Databricks SQLnoSQL-like query language (GSQL)no
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
gRPC
OpenAPI 3.0
RESTful HTTP/JSON API infoOpenAPI 3.0
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
TinkerPop 3
Supported programming languagesPython
R
Scala
.Net
Go
Java
JavaScript (Node.js)
Python
Rust
C++
Java
Groovy
Java
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesno
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesCollection-level replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency, tunable consistencynone
Foreign keys infoReferential integrityyes infoRelationships in graphsyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesno
Durability infoSupport for making data persistentyesyesyesoptional
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
User concepts infoAccess controlKey-based authenticationRole-based access controlno
More information provided by the system vendor
DatabricksQdrantTigerGraphTinkerGraph
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksQdrantTigerGraphTinkerGraph
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