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DBMS > Databricks vs. OpenEdge vs. Oracle Berkeley DB vs. QuestDB

System Properties Comparison Databricks vs. OpenEdge vs. Oracle Berkeley DB vs. QuestDB

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonOpenEdge  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonQuestDB  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.Application development environment with integrated database management systemWidely used in-process key-value storeA high performance open source SQL database for time series data
Primary database modelDocument store
Relational DBMS
Relational DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Time Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score3.45
Rank#85  Overall
#46  Relational DBMS
Score2.01
Rank#126  Overall
#21  Key-value stores
#3  Native XML DBMS
Score2.70
Rank#105  Overall
#8  Time Series DBMS
Websitewww.databricks.comwww.progress.com/­openedgewww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlquestdb.io
Technical documentationdocs.databricks.comdocumentation.progress.com/­output/­ua/­OpenEdge_latestdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlquestdb.io/­docs
DeveloperDatabricksProgress Software CorporationOracle infooriginally developed by Sleepycat, which was acquired by OracleQuestDB Technology Inc
Initial release2013198419942014
Current releaseOpenEdge 12.2, March 202018.1.40, May 2020
License infoCommercial or Open SourcecommercialcommercialOpen Source infocommercial license availableOpen 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 languageC, Java, C++ (depending on the Berkeley DB edition)Java (Zero-GC), C++, Rust
Server operating systemshostedAIX
HP-UX
Linux
Solaris
Windows
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
macOS
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeyes infoschema-free via InfluxDB Line Protocol
Typing infopredefined data types such as float or dateyesnoyes
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.yesyesyes infoonly with the Berkeley DB XML editionno
Secondary indexesyesyesyesno
SQL infoSupport of SQLwith Databricks SQLyes infoclose to SQL 92yes infoSQL interfaced based on SQLite is availableSQL with time-series extensions
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Supported programming languagesPython
R
Scala
Progress proprietary ABL (Advanced Business Language).Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesnono
Triggersyesyes infoonly for the SQL APIno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning infosince Version 11.4nonehorizontal partitioning (by timestamps)
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationSource-replica replicationSource-replica replication with eventual consistency
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID for single-table writes
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.nonoyesyes infothrough memory mapped files
User concepts infoAccess controlUsers and groupsno
More information provided by the system vendor
DatabricksOpenEdgeOracle Berkeley DBQuestDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
Relational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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