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DBMS > Geode vs. Google Cloud Bigtable vs. HarperDB vs. Hawkular Metrics vs. Spark SQL

System Properties Comparison Geode vs. Google Cloud Bigtable vs. HarperDB vs. Hawkular Metrics vs. Spark SQL

Editorial information provided by DB-Engines
NameGeode  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHarperDB  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionGeode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeKey-value store
Wide column store
Document storeTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.92
Rank#131  Overall
#23  Key-value stores
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.55
Rank#248  Overall
#38  Document stores
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitegeode.apache.orgcloud.google.com/­bigtablewww.harperdb.iowww.hawkular.orgspark.apache.org/­sql
Technical documentationgeode.apache.org/­docscloud.google.com/­bigtable/­docsdocs.harperdb.io/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.GoogleHarperDBCommunity supported by Red HatApache Software Foundation
Initial release20022015201720142014
Current release1.1, February 20173.1, August 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses available as Gemfirecommercialcommercial infofree community edition availableOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaNode.jsJavaScala
Server operating systemsAll OS with a Java VM infothe JDK (8 or later) is also requiredhostedLinux
OS X
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freedynamic schemaschema-freeyes
Typing infopredefined data types such as float or dateyesnoyes infoJSON data typesyesyes
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.nonononono
Secondary indexesnonoyesnono
SQL infoSupport of SQLSQL-like query language (OQL)noSQL-like data manipulation statementsnoSQL-like DML and DDL statements
APIs and other access methodsJava Client API
Memcached protocol
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
HTTP RESTJDBC
ODBC
Supported programming languages.Net
All JVM based languages
C++
Groovy
Java
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
Go
Java
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsnoCustom Functions infosince release 3.1nono
Triggersyes infoCache Event Listenersnonoyes infovia Hawkular Alertingno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingA table resides as a whole on one (or more) nodes in a clusterSharding infobased on Cassandrayes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationInternal replication in Colossus, and regional replication between two clusters in different zonesyes infothe nodes on which a table resides can be definedselectable replication factor infobased on Cassandranone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes, on a single nodeAtomic single-row operationsAtomic execution of specific operationsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes, using LMDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesnono
User concepts infoAccess controlAccess rights per client and object definableAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and rolesnono

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More resources
GeodeGoogle Cloud BigtableHarperDBHawkular MetricsSpark SQL
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