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DBMS > FeatureBase vs. GigaSpaces vs. H2 vs. LevelDB vs. Netezza

System Properties Comparison FeatureBase vs. GigaSpaces vs. H2 vs. LevelDB vs. Netezza

Editorial information provided by DB-Engines
NameFeatureBase  Xexclude from comparisonGigaSpaces  Xexclude from comparisonH2  Xexclude from comparisonLevelDB  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparison
DescriptionReal-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsFull-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.Embeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesData warehouse and analytics appliance part of IBM PureSystems
Primary database modelRelational DBMSDocument store
Object oriented DBMS infoValues are user defined objects
Relational DBMSKey-value storeRelational DBMS
Secondary database modelsGraph DBMS
Search engine
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#309  Overall
#139  Relational DBMS
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score8.13
Rank#49  Overall
#31  Relational DBMS
Score2.35
Rank#111  Overall
#19  Key-value stores
Score9.06
Rank#46  Overall
#29  Relational DBMS
Websitewww.featurebase.comwww.gigaspaces.comwww.h2database.comgithub.com/­google/­leveldbwww.ibm.com/­products/­netezza
Technical documentationdocs.featurebase.comdocs.gigaspaces.com/­latest/­landing.htmlwww.h2database.com/­html/­main.htmlgithub.com/­google/­leveldb/­blob/­main/­doc/­index.md
DeveloperMolecula and Pilosa Open Source ContributorsGigaspaces TechnologiesThomas MuellerGoogleIBM
Initial release20172000200520112000
Current release2022, May 202215.5, September 20202.2.220, July 20231.23, February 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; Commercial licenses availableOpen Source infodual-licence (Mozilla public license, Eclipse public license)Open Source infoBSDcommercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoJava, C++, .NetJavaC++
Server operating systemsLinux
macOS
Linux
macOS
Solaris
Windows
All OS with a Java VMIllumos
Linux
OS X
Windows
Linux infoincluded in appliance
Data schemeyesschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesnoyes
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.nono infoXML can be used for describing objects metadatanono
Secondary indexesnoyesyesnoyes
SQL infoSupport of SQLSQL queriesSQL-99 for query and DML statementsyesnoyes
APIs and other access methodsgRPC
JDBC
Kafka Connector
ODBC
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
JDBC
ODBC
JDBC
ODBC
OLE DB
Supported programming languagesJava
Python
.Net
C++
Java
Python
Scala
JavaC++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresyesJava Stored Procedures and User-Defined Functionsnoyes
Triggersnoyes, event driven architectureyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnonenoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
With clustering: 2 database servers on different computers operate on identical copies of a databasenoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoMap-Reduce pattern can be built with XAP task executorsnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyes, using Linux fsyncyesyesyes infowith automatic compression on writesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlRole-based access controlfine grained access rights according to SQL-standardnoUsers with fine-grained authorization concept

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More resources
FeatureBaseGigaSpacesH2LevelDBNetezza infoAlso called PureData System for Analytics by IBM
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