DBMS > Apache Impala vs. GeoMesa vs. GridDB vs. Oracle

System Properties Comparison Apache Impala vs. GeoMesa vs. GridDB vs. Oracle

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

Scalable in-memory time series database optimized for IoT and Big Data

Widely used RDBMS

Primary database model

Secondary database models

Document store

Key-value store
Relational DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	2.09
Rank	#120	Overall
	#10	Time Series DBMS

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Website

impala.apache.org

www.geomesa.org

griddb.net

www.oracle.com/database

Technical documentation

impala.apache.org/impala-docs.html

www.geomesa.org/documentation/stable/user/index.html

docs.griddb.net

docs.oracle.com/en/database

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

CCRi and others

Toshiba Corporation

Oracle

Initial release

2013

2014

2013

1980

Current release

4.1.0, June 2022

5.0.0, May 2024

5.1, August 2022

23c, September 2023

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache License 2.0

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Scala

C++

C and C++

Server operating systems

Linux

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Data scheme

yes

Schemaless in JSON and XML columns

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL92, SQL-like TQL (Toshiba Query Language)

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

All languages supporting JDBC/ODBC

C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

PL/SQL

also stored procedures in Java possible

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

depending on storage layer

Sharding

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

depending on storage layer

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

depending on storage layer

Immediate consistency within container, eventual consistency across containers

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID at container level

ACID

isolation level can be parameterized

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

depending on storage layer

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

yes

depending on the DBMS used for storage

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more

Competitive advantages

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more

Typical application scenarios

Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more

Key customers

Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more

Market metrics

GitHub trending repository
» more

Licensing and pricing models

Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
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