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DBMS > Bangdb vs. Greenplum vs. Hazelcast vs. IRONdb vs. Spark SQL

System Properties Comparison Bangdb vs. Greenplum vs. Hazelcast vs. IRONdb vs. Spark SQL

Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonGreenplum  Xexclude from comparisonHazelcast  Xexclude from comparisonIRONdb  Xexclude from comparisonSpark SQL  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionConverged and high performance database for device data, events, time series, document and graphAnalytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.A widely adopted in-memory data gridA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicitySpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Relational DBMSKey-value storeTime Series DBMSRelational DBMS
Secondary database modelsSpatial DBMSDocument store
Spatial DBMS
Document store infoJSON support with IMDG 3.12
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
Score8.08
Rank#48  Overall
#31  Relational DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitebangdb.comgreenplum.orghazelcast.comwww.circonus.com/solutions/time-series-database/spark.apache.org/­sql
Technical documentationdocs.bangdb.comdocs.greenplum.orghazelcast.org/­imdg/­docsdocs.circonus.com/irondb/category/getting-startedspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperSachin Sinha, BangDBPivotal Software Inc.HazelcastCirconus LLC.Apache Software Foundation
Initial release20122005200820172014
Current releaseBangDB 2.0, October 20217.0.0, September 20235.3.6, November 2023V0.10.20, January 20183.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoBSD 3Open Source infoApache 2.0Open Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++JavaC and C++Scala
Server operating systemsLinuxLinuxAll OS with a Java VMLinuxLinux
OS X
Windows
Data schemeschema-freeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsyesyesyes infotext, numeric, histogramsyes
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.noyes infosince Version 4.2yes infothe object must implement a serialization strategynono
Secondary indexesyes infosecondary, composite, nested, reverse, geospatialyesyesnono
SQL infoSupport of SQLSQL like support with command line toolyesSQL-like query languageSQL-like query language (Circonus Analytics Query Language: CAQL)SQL-like DML and DDL statements
APIs and other access methodsProprietary protocol
RESTful HTTP API
JDBC
ODBC
JCache
JPA
Memcached protocol
RESTful HTTP API
HTTP APIJDBC
ODBC
Supported programming languagesC
C#
C++
Java
Python
C
Java
Perl
Python
R
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyesyes infoEvent Listeners, Executor Servicesyes, in Luano
Triggersyes, Notifications (with Streaming only)yesyes infoEventsnono
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmShardingShardingAutomatic, metric affinity per nodeyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)Source-replica replicationyes infoReplicated Mapconfigurable replication factor, datacenter awarenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglyImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDone or two-phase-commit; repeatable reads; read commitednono
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyesyesyesyes
Durability infoSupport for making data persistentyes, implements WAL (Write ahead log) as wellyesyesyesyes
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 modenoyesnono
User concepts infoAccess controlyes (enterprise version only)fine grained access rights according to SQL-standardRole-based access controlnono

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More resources
BangdbGreenplumHazelcastIRONdbSpark SQL
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