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DBMS > Apache Impala vs. Google Cloud Datastore vs. H2GIS vs. Hazelcast vs. Realm

System Properties Comparison Apache Impala vs. Google Cloud Datastore vs. H2GIS vs. Hazelcast vs. Realm

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonH2GIS  Xexclude from comparisonHazelcast  Xexclude from comparisonRealm  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformSpatial extension of H2A widely adopted in-memory data gridA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data
Primary database modelRelational DBMSDocument storeSpatial DBMSKey-value storeDocument store
Secondary database modelsDocument storeRelational DBMSDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score0.00
Rank#383  Overall
#7  Spatial DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score7.60
Rank#52  Overall
#9  Document stores
Websiteimpala.apache.orgcloud.google.com/­datastorewww.h2gis.orghazelcast.comrealm.io
Technical documentationimpala.apache.org/­impala-docs.htmlcloud.google.com/­datastore/­docswww.h2gis.org/­docs/­homehazelcast.org/­imdg/­docsrealm.io/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleCNRSHazelcastRealm, acquired by MongoDB in May 2019
Initial release20132008201320082014
Current release4.1.0, June 20225.3.6, November 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoLGPL 3.0Open Source infoApache Version 2; commercial licenses availableOpen Source
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaJava
Server operating systemsLinuxhostedAll OS with a Java VMAndroid
Backend: server-less
iOS
Windows
Data schemeyesschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyes, details hereyesyesyes
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.nononoyes infothe object must implement a serialization strategyno
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query language (GQL)yesSQL-like query languageno
APIs and other access methodsJDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JCache
JPA
Memcached protocol
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBC.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
Java infowith Android only
Objective-C
React Native
Swift
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceusing Google App Engineyes infobased on H2yes infoEvent Listeners, Executor Servicesno inforuns within the applications so server-side scripts are unnecessary
TriggersnoCallbacks using the Google Apps Engineyesyes infoEventsyes infoChange Listeners
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication using Paxosyes infobased on H2yes infoReplicated Mapnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyes infousing Google Cloud Dataflownoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDone or two-phase-commit; repeatable reads; read commitedACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyesyes infoIn-Memory realm
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yes infobased on H2Role-based access controlyes

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More resources
Apache ImpalaGoogle Cloud DatastoreH2GISHazelcastRealm
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