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DBMS > Databend vs. jBASE vs. Microsoft Azure Data Explorer vs. Oracle Berkeley DB vs. Sqrrl

System Properties Comparison Databend vs. jBASE vs. Microsoft Azure Data Explorer vs. Oracle Berkeley DB vs. Sqrrl

Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonjBASE  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSqrrl  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityA robust multi-value DBMS comprising development tools and middlewareFully managed big data interactive analytics platformWidely used in-process key-value storeAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelRelational DBMSMultivalue DBMSRelational DBMS infocolumn orientedKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Document store
Graph DBMS
Key-value store
Wide column store
Secondary database modelsDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.28
Rank#287  Overall
#131  Relational DBMS
Score1.36
Rank#157  Overall
#3  Multivalue DBMS
Score3.28
Rank#83  Overall
#45  Relational DBMS
Score1.88
Rank#130  Overall
#23  Key-value stores
#3  Native XML DBMS
Websitegithub.com/­datafuselabs/­databend
www.databend.com
www.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-jbaseazure.microsoft.com/­services/­data-explorerwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlsqrrl.com
Technical documentationdocs.databend.comdocs.rocketsoftware.com/­bundle?labelkey=jbase_5.9docs.microsoft.com/­en-us/­azure/­data-explorerdocs.oracle.com/­cd/­E17076_05/­html/­index.html
DeveloperDatabend LabsRocket Software (formerly Zumasys)MicrosoftOracle infooriginally developed by Sleepycat, which was acquired by OracleAmazon infooriginally Sqrrl Data, Inc.
Initial release20211991201919942012
Current release1.0.59, April 20235.7cloud service with continuous releases18.1.40, May 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infocommercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageRustC, Java, C++ (depending on the Berkeley DB edition)Java
Server operating systemshosted
Linux
macOS
AIX
Linux
Windows
hostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
Data schemeyesschema-freeFixed schema with schema-less datatypes (dynamic)schema-freeschema-free
Typing infopredefined data types such as float or dateyesoptionalyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesnoyes
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.noyesyesyes infoonly with the Berkeley DB XML edition
Secondary indexesnoall fields are automatically indexedyesyes
SQL infoSupport of SQLyesEmbedded SQL for jBASE in BASICKusto Query Language (KQL), SQL subsetyes infoSQL interfaced based on SQLite is availableno
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
.Net
Basic
Jabbascript
Java
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.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
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresnoyesYes, possible languages: KQL, Python, Rnono
Triggersnoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoonly for the SQL APIno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoImplicit feature of the cloud servicenoneSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDnoACIDAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.yesnoyes
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesAccess rights can be defined down to the item levelAzure Active Directory AuthenticationnoCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
DatabendjBASEMicrosoft Azure Data ExplorerOracle Berkeley DBSqrrl
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