DB-EnginesExtremeDB: mitigate connectivity issues in a DBMSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > GeoMesa vs. Google Cloud Bigtable vs. Greenplum vs. InfinityDB vs. Spark SQL

System Properties Comparison GeoMesa vs. Google Cloud Bigtable vs. Greenplum vs. InfinityDB vs. Spark SQL

Editorial information provided by DB-Engines
NameGeoMesa  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGreenplum  Xexclude from comparisonInfinityDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionGeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.A Java embedded Key-Value Store which extends the Java Map interfaceSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelSpatial DBMSKey-value store
Wide column store
Relational DBMSKey-value storeRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.86
Rank#205  Overall
#4  Spatial DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score8.08
Rank#48  Overall
#31  Relational DBMS
Score0.08
Rank#365  Overall
#55  Key-value stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.geomesa.orgcloud.google.com/­bigtablegreenplum.orgboilerbay.comspark.apache.org/­sql
Technical documentationwww.geomesa.org/­documentation/­stable/­user/­index.htmlcloud.google.com/­bigtable/­docsdocs.greenplum.orgboilerbay.com/­infinitydb/­manualspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperCCRi and othersGooglePivotal Software Inc.Boiler Bay Inc.Apache Software Foundation
Initial release20142015200520022014
Current release5.0.0, May 20247.0.0, September 20234.03.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache License 2.0commercialOpen Source infoApache 2.0commercialOpen Source infoApache 2.0
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 languageScalaJavaScala
Server operating systemshostedLinuxAll OS with a Java VMLinux
OS X
Windows
Data schemeyesschema-freeyesyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeyes
Typing infopredefined data types such as float or dateyesnoyesyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyes
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.nonoyes infosince Version 4.2nono
Secondary indexesyesnoyesno infomanual creation possible, using inversions based on multi-value capabilityno
SQL infoSupport of SQLnonoyesnoSQL-like DML and DDL statements
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
JDBC
ODBC
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C
Java
Perl
Python
R
JavaJava
Python
R
Scala
Server-side scripts infoStored proceduresnonoyesnono
Triggersnonoyesnono
Partitioning methods infoMethods for storing different data on different nodesdepending on storage layerShardingShardingnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesdepending on storage layerInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemdepending on storage layerImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate Consistency infoREAD-COMMITTED or SERIALIZED
Foreign keys infoReferential integritynonoyesno infomanual creation possible, using inversions based on multi-value capabilityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsACIDACID infoOptimistic locking for transactions; no isolation for bulk loadsno
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.depending on storage layernononono
User concepts infoAccess controlyes infodepending on the DBMS used for storageAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardnono

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
GeoMesaGoogle Cloud BigtableGreenplumInfinityDBSpark SQL
DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

show all

Recent citations in the news

Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs
31 January 2022, InfoQ.com

Google scales up Cloud Bigtable NoSQL database
27 January 2022, TechTarget

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

Google Cloud makes it cheaper to run smaller workloads on Bigtable
7 April 2020, TechCrunch

Google introduces Cloud Bigtable managed NoSQL database to process data at scale
6 May 2015, VentureBeat

provided by Google News

1. Introducing the Greenplum Database - Data Warehousing with Greenplum [Book]
6 December 2018, oreilly.com

VMware Greenplum on AWS: Parallel Postgres for Enterprise Analytics at Scale | Amazon Web Services
9 September 2019, AWS Blog

RSA: EMC integrates Hadoop with Greenplum database
26 February 2013, DatacenterDynamics

Greenplum 6 ventures outside the analytic box | ZDNET
19 March 2019, ZDNet

Greenplum 6 review: Jack of all trades, master of some
7 November 2019, InfoWorld

provided by Google News

Use Amazon Athena with Spark SQL for your open-source transactional table formats | Amazon Web Services
24 January 2024, AWS Blog

What is Apache Spark? The big data platform that crushed Hadoop
3 April 2024, InfoWorld

Cracking the Apache Spark Interview: 80+ Top Questions and Answers for 2024
1 April 2024, Simplilearn

Performant IPv4 Range Spark Joins | by Jean-Claude Cote
24 January 2024, Towards Data Science

Simba Technologies(R) Introduces New, Powerful JDBC Driver With SQL Connector for Apache Spark(TM)
17 March 2024, Yahoo Singapore News

provided by Google News



Share this page

Featured Products

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Present your product here