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DBMS > Bangdb vs. LevelDB vs. Microsoft Azure Synapse Analytics vs. Spark SQL

System Properties Comparison Bangdb vs. LevelDB vs. Microsoft Azure Synapse Analytics vs. Spark SQL

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Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonLevelDB  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Key-value storeRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#338  Overall
#47  Document stores
#32  Graph DBMS
#31  Time Series DBMS
Score2.25
Rank#115  Overall
#19  Key-value stores
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitebangdb.comgithub.com/­google/­leveldbazure.microsoft.com/­services/­synapse-analyticsspark.apache.org/­sql
Technical documentationdocs.bangdb.comgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mddocs.microsoft.com/­azure/­synapse-analyticsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperSachin Sinha, BangDBGoogleMicrosoftApache Software Foundation
Initial release2012201120162014
Current releaseBangDB 2.0, October 20211.23, February 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoBSD 3Open Source infoBSDcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++C++C++Scala
Server operating systemsLinuxIllumos
Linux
OS X
Windows
hostedLinux
OS X
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsnoyesyes
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.nononono
Secondary indexesyes infosecondary, composite, nested, reverse, geospatialnoyesno
SQL infoSupport of SQLSQL like support with command line toolnoyesSQL-like DML and DDL statements
APIs and other access methodsProprietary protocol
RESTful HTTP API
ADO.NET
JDBC
ODBC
JDBC
ODBC
Supported programming languagesC
C#
C++
Java
Python
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
C#
Java
PHP
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonoTransact SQLno
Triggersyes, Notifications (with Streaming only)nonono
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmnoneSharding, horizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)noneyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyesyesyes
Durability infoSupport for making data persistentyes, implements WAL (Write ahead log) as wellyes infowith automatic compression on writesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes, run db with in-memory only modeno
User concepts infoAccess controlyes (enterprise version only)noyesno

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More resources
BangdbLevelDBMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSpark SQL
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