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DBMS > Bangdb vs. Databricks vs. etcd vs. H2

System Properties Comparison Bangdb vs. Databricks vs. etcd vs. H2

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Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonDatabricks  Xexclude from comparisonetcd  Xexclude from comparisonH2  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphThe 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 distributed reliable key-value storeFull-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Document store
Relational DBMS
Key-value storeRelational DBMS
Secondary database modelsSpatial DBMSSpatial 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
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score7.03
Rank#54  Overall
#5  Key-value stores
Score8.33
Rank#46  Overall
#30  Relational DBMS
Websitebangdb.comwww.databricks.cometcd.io
github.com/­etcd-io/­etcd
www.h2database.com
Technical documentationdocs.bangdb.comdocs.databricks.cometcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
www.h2database.com/­html/­main.html
DeveloperSachin Sinha, BangDBDatabricksThomas Mueller
Initial release201220132005
Current releaseBangDB 2.0, October 20213.4, August 20192.2.220, July 2023
License infoCommercial or Open SourceOpen Source infoBSD 3commercialOpen Source infoApache Version 2.0Open Source infodual-licence (Mozilla public license, Eclipse public license)
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++GoJava
Server operating systemsLinuxhostedFreeBSD
Linux
Windows infoexperimental
All OS with a Java VM
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)schema-freeyes
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsnoyes
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.noyesnono
Secondary indexesyes infosecondary, composite, nested, reverse, geospatialyesnoyes
SQL infoSupport of SQLSQL like support with command line toolwith Databricks SQLnoyes
APIs and other access methodsProprietary protocol
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
gRPC
JSON over HTTP
JDBC
ODBC
Supported programming languagesC
C#
C++
Java
Python
Python
R
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
Java
Server-side scripts infoStored proceduresnouser defined functions and aggregatesnoJava Stored Procedures and User-Defined Functions
Triggersyes, Notifications (with Streaming only)yes, watching key changesyes
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)yesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.With clustering: 2 database servers on different computers operate on identical copies of a database
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 ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyes, implements WAL (Write ahead log) as wellyesyesyes
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 modenonoyes
User concepts infoAccess controlyes (enterprise version only)nofine grained access rights according to SQL-standard
More information provided by the system vendor
BangdbDatabricksetcdH2
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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BangdbDatabricksetcdH2
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