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DBMS > GridGain vs. IRONdb vs. LevelDB vs. Microsoft Azure Synapse Analytics vs. SiteWhere

System Properties Comparison GridGain vs. IRONdb vs. LevelDB vs. Microsoft Azure Synapse Analytics vs. SiteWhere

Editorial information provided by DB-Engines
NameGridGain  Xexclude from comparisonIRONdb  Xexclude from comparisonLevelDB  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonSiteWhere  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionGridGain is an in-memory computing platform, built on Apache IgniteA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityEmbeddable 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 ServerM2M integration platform for persisting/querying time series data
Primary database modelKey-value store
Relational DBMS
Time Series DBMSKey-value storeRelational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score2.35
Rank#111  Overall
#19  Key-value stores
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score0.06
Rank#356  Overall
#35  Time Series DBMS
Websitewww.gridgain.comwww.circonus.com/solutions/time-series-database/github.com/­google/­leveldbazure.microsoft.com/­services/­synapse-analyticsgithub.com/­sitewhere/­sitewhere
Technical documentationwww.gridgain.com/­docs/­index.htmldocs.circonus.com/irondb/category/getting-startedgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mddocs.microsoft.com/­azure/­synapse-analyticssitewhere1.sitewhere.io/­index.html
DeveloperGridGain Systems, Inc.Circonus LLC.GoogleMicrosoftSiteWhere
Initial release20072017201120162010
Current releaseGridGain 8.5.1V0.10.20, January 20181.23, February 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoBSDcommercialOpen Source infoCommon Public Attribution License Version 1.0
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .NetC and C++C++C++Java
Server operating systemsLinux
OS X
Solaris
Windows
LinuxIllumos
Linux
OS X
Windows
hostedLinux
OS X
Windows
Data schemeyesschema-freeschema-freeyespredefined scheme
Typing infopredefined data types such as float or dateyesyes infotext, numeric, histogramsnoyesyes
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.yesnononono
Secondary indexesyesnonoyesno
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLSQL-like query language (Circonus Analytics Query Language: CAQL)noyesno
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
HTTP APIADO.NET
JDBC
ODBC
HTTP REST
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
C#
Java
PHP
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)yes, in LuanoTransact SQL
Triggersyes (cache interceptors and events)nonono
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodenoneSharding, horizontal partitioningSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)configurable replication factor, datacenter awarenoneyesselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)nononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency per node, eventual consistency across nodesImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono 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 dataACIDnonoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infowith automatic compression on writesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlSecurity Hooks for custom implementationsnonoyesUsers with fine-grained authorization concept

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GridGainIRONdbLevelDBMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSiteWhere
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