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DBMS > Databricks vs. Informix vs. LevelDB vs. Tkrzw

System Properties Comparison Databricks vs. Informix vs. LevelDB vs. Tkrzw

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonInformix  Xexclude from comparisonLevelDB  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.A secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things dataEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesA 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
Relational DBMS infoSince Version 12.10 support for JSON/BSON datatypes compatible with MongoDBKey-value storeKey-value store
Secondary database modelsDocument store
Spatial DBMS
Time Series DBMS infowith Informix TimeSeries Extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score84.24
Rank#14  Overall
#2  Document stores
#9  Relational DBMS
Score16.32
Rank#35  Overall
#21  Relational DBMS
Score2.33
Rank#111  Overall
#19  Key-value stores
Score0.00
Rank#385  Overall
#61  Key-value stores
Websitewww.databricks.comwww.ibm.com/­products/­informixgithub.com/­google/­leveldbdbmx.net/­tkrzw
Technical documentationdocs.databricks.cominformix.hcldoc.com
www.ibm.com/­support/­knowledgecenter/­SSGU8G/­welcomeIfxServers.html
github.com/­google/­leveldb/­blob/­main/­doc/­index.md
DeveloperDatabricksIBM, HCL Technologies infoEffective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.GoogleMikio Hirabayashi
Initial release2013198420112020
Current release14.10.FC5, November 20201.23, February 20210.9.3, August 2020
License infoCommercial or Open Sourcecommercialcommercial infofree developer edition availableOpen Source infoBSDOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++ and JavaC++C++
Server operating systemshostedAIX
HP-UX
Linux
macOS
Solaris
Windows
Illumos
Linux
OS X
Windows
Linux
macOS
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeschema-free
Typing infopredefined data types such as float or dateyes infoSince Version 12.10 support for JSON/BSON datatypesnono
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.yesnono
Secondary indexesyesyesno
SQL infoSupport of SQLwith Databricks SQLyesnono
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
JSON API infoMongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
Supported programming languagesPython
R
Scala
.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesnono
Triggersyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
nonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infowith automatic compression on writesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infousing specific database classes
User concepts infoAccess controlUsers with fine-grained authentication, authorization, and auditing controlsnono
More information provided by the system vendor
DatabricksInformixLevelDBTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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