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DBMS > Databricks vs. Microsoft Azure Cosmos DB vs. RocksDB vs. SAP IQ vs. Tkrzw

System Properties Comparison Databricks vs. Microsoft Azure Cosmos DB vs. RocksDB vs. SAP IQ vs. Tkrzw

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB  Xexclude from comparisonRocksDB  Xexclude from comparisonSAP IQ infoformer name: Sybase IQ  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  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.Globally distributed, horizontally scalable, multi-model database serviceEmbeddable persistent key-value store optimized for fast storage (flash and RAM)Columnar RDBMS optimized for Big Data analyticsA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelDocument store
Relational DBMS
Document store
Graph DBMS
Key-value store
Wide column store
Key-value storeRelational DBMS infocolumn-orientedKey-value store
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
Score29.04
Rank#27  Overall
#4  Document stores
#2  Graph DBMS
#3  Key-value stores
#3  Wide column stores
Score3.65
Rank#85  Overall
#11  Key-value stores
Score2.75
Rank#104  Overall
#53  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitewww.databricks.comazure.microsoft.com/­services/­cosmos-dbrocksdb.orgwww.sap.com/­products/­technology-platform/­sybase-iq-big-data-management.htmldbmx.net/­tkrzw
Technical documentationdocs.databricks.comlearn.microsoft.com/­azure/­cosmos-dbgithub.com/­facebook/­rocksdb/­wikihelp.sap.com/­docs/­SAP_IQ
DeveloperDatabricksMicrosoftFacebook, Inc.SAP, formerly SybaseMikio Hirabayashi
Initial release20132014201319942020
Current release8.11.4, April 202416.1 SPS04, April 20190.9.3, August 2020
License infoCommercial or Open SourcecommercialcommercialOpen Source infoBSDcommercialOpen Source infoApache Version 2.0
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 languageC++C++
Server operating systemshostedhostedLinuxAIX
HP-UX
Linux
Solaris
Windows
Linux
macOS
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or dateyes infoJSON typesnoyesno
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 infoAll properties auto-indexed by defaultnoyes
SQL infoSupport of SQLwith Databricks SQLSQL-like query languagenoyesno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API
C++ API
Java API
ADO.NET
JDBC
ODBC
RESTful HTTP API
Supported programming languagesPython
R
Scala
.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python
C
C++
Go
Java
Perl
Python
Ruby
C
C#
C++
Java
Perl
PHP
Python
Ruby
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesJavaScriptnoyesno
TriggersJavaScriptyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud servicehorizontal partitioningshared disk or shared nothing architectures with SAP IQ Multiplexernone
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoImplicit feature of the cloud serviceyesSAP/Sybase Replication Servernone
MapReduce infoOffers an API for user-defined Map/Reduce methodswith Hadoop integration infoIntegration with Hadoop/HDInsight on Azure*noHadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyBounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency infoConsistency level configurable on request level
Session Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDMulti-item ACID transactions with snapshot isolation within a partitionyesACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes infousing specific database classes
User concepts infoAccess controlAccess rights can be defined down to the item levelnofine grained access rights according to SQL-standardno
More information provided by the system vendor
DatabricksMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDBRocksDBSAP IQ infoformer name: Sybase IQTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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3rd partiesCData: Connect to Big Data & NoSQL through standard Drivers.
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Speedb: A high performance RocksDB-compliant key-value store optimized for write-intensive workloads.
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More resources
DatabricksMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDBRocksDBSAP IQ infoformer name: Sybase IQTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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