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DBMS > Apache Impala vs. Axibase vs. Google Cloud Datastore vs. Hazelcast vs. Newts

System Properties Comparison Apache Impala vs. Axibase vs. Google Cloud Datastore vs. Hazelcast vs. Newts

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonAxibase  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHazelcast  Xexclude from comparisonNewts  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopScalable TimeSeries DBMS based on HBase with integrated rule engine and visualizationAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA widely adopted in-memory data gridTime Series DBMS based on Cassandra
Primary database modelRelational DBMSTime Series DBMSDocument storeKey-value storeTime Series DBMS
Secondary database modelsDocument storeDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.35
Rank#282  Overall
#25  Time Series DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score5.46
Rank#61  Overall
#7  Key-value stores
Score0.07
Rank#375  Overall
#41  Time Series DBMS
Websiteimpala.apache.orgaxibase.com/­docs/­atsd/­financecloud.google.com/­datastorehazelcast.comopennms.github.io/­newts
Technical documentationimpala.apache.org/­impala-docs.htmlcloud.google.com/­datastore/­docshazelcast.org/­imdg/­docsgithub.com/­OpenNMS/­newts/­wiki
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaAxibase CorporationGoogleHazelcastOpenNMS Group
Initial release20132013200820082014
Current release4.1.0, June 2022155855.3.6, November 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infoCommunity Edition (single node) is free, Enterprise Edition (distributed) is paidcommercialOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaJavaJava
Server operating systemsLinuxLinuxhostedAll OS with a Java VMLinux
OS X
Windows
Data schemeyesyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyes infoshort, integer, long, float, double, decimal, stringyes, details hereyesyes
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 indexesyesnoyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languageSQL-like query language (GQL)SQL-like query languageno
APIs and other access methodsJDBC
ODBC
JDBC
Proprietary protocol (Network API)
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JCache
JPA
Memcached protocol
RESTful HTTP API
HTTP REST
Java API
Supported programming languagesAll languages supporting JDBC/ODBCGo
Java
PHP
Python
R
Ruby
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Java
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesusing Google App Engineyes infoEvent Listeners, Executor Servicesno
TriggersnoyesCallbacks using the Google Apps Engineyes infoEventsno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingShardingSharding infobased on Cassandra
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationMulti-source replication using Paxosyes infoReplicated Mapselectable replication factor infobased on Cassandra
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesyes infousing Google Cloud Dataflowyesno
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 Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsone or two-phase-commit; repeatable reads; read commitedno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.nonoyesno
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)Role-based access controlno

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More resources
Apache ImpalaAxibaseGoogle Cloud DatastoreHazelcastNewts
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