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DBMS > GigaSpaces vs. Hazelcast vs. Ingres vs. LevelDB vs. Microsoft Azure Data Explorer

System Properties Comparison GigaSpaces vs. Hazelcast vs. Ingres vs. LevelDB vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameGigaSpaces  Xexclude from comparisonHazelcast  Xexclude from comparisonIngres  Xexclude from comparisonLevelDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsA widely adopted in-memory data gridWell established RDBMSEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesFully managed big data interactive analytics platform
Primary database modelDocument store
Object oriented DBMS infoValues are user defined objects
Key-value storeRelational DBMSKey-value storeRelational DBMS infocolumn oriented
Secondary database modelsGraph DBMS
Search engine
Document store infoJSON support with IMDG 3.12Document 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
Score1.03
Rank#188  Overall
#32  Document stores
#6  Object oriented DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Score3.80
Rank#82  Overall
#44  Relational DBMS
Score2.25
Rank#115  Overall
#19  Key-value stores
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websitewww.gigaspaces.comhazelcast.comwww.actian.com/­databases/­ingresgithub.com/­google/­leveldbazure.microsoft.com/­services/­data-explorer
Technical documentationdocs.gigaspaces.com/­latest/­landing.htmlhazelcast.org/­imdg/­docsdocs.actian.com/­ingresgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mddocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperGigaspaces TechnologiesHazelcastActian CorporationGoogleMicrosoft
Initial release200020081974 infooriginally developed at University Berkely in early 1970s20112019
Current release15.5, September 20205.3.6, November 202311.2, May 20221.23, February 2021cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2; Commercial licenses availableOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoBSDcommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .NetJavaCC++
Server operating systemsLinux
macOS
Solaris
Windows
All OS with a Java VMAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
Illumos
Linux
OS X
Windows
hosted
Data schemeschema-freeschema-freeyesschema-freeFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyesyesnoyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types
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.no infoXML can be used for describing objects metadatayes infothe object must implement a serialization strategyno infobut tools for importing/exporting data from/to XML-files availablenoyes
Secondary indexesyesyesyesnoall fields are automatically indexed
SQL infoSupport of SQLSQL-99 for query and DML statementsSQL-like query languageyesnoKusto Query Language (KQL), SQL subset
APIs and other access methodsGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
JCache
JPA
Memcached protocol
RESTful HTTP API
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languages.Net
C++
Java
Python
Scala
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresyesyes infoEvent Listeners, Executor ServicesyesnoYes, possible languages: KQL, Python, R
Triggersyes, event driven architectureyes infoEventsyesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslynoneSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
yes infoReplicated MapIngres Replicatornoneyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoMap-Reduce pattern can be built with XAP task executorsyesnonoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDone or two-phase-commit; repeatable reads; read commitedACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMVCCyesyes
Durability infoSupport for making data persistentyesyesyesyes infowith automatic compression on writesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnono
User concepts infoAccess controlRole-based access controlRole-based access controlfine grained access rights according to SQL-standardnoAzure Active Directory Authentication

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GigaSpacesHazelcastIngresLevelDBMicrosoft Azure Data Explorer
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