DBMS > Apache Impala vs. BigchainDB vs. GeoSpock vs. Oracle vs. Snowflake

System Properties Comparison Apache Impala vs. BigchainDB vs. GeoSpock vs. Oracle vs. Snowflake

Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

Analytic DBMS for Hadoop

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

Spatial and temporal data processing engine for extreme data scale

Widely used RDBMS

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Relational DBMS

Document store

Relational DBMS

Secondary database models

Document store

Time Series 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	0.85
Rank	#208	Overall
	#35	Document stores

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

impala.apache.org

www.bigchaindb.com

geospock.com

www.oracle.com/database

www.snowflake.com

Technical documentation

impala.apache.org/impala-docs.html

bigchaindb.readthedocs.io/en/latest

docs.oracle.com/en/database

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

GeoSpock

Oracle

Snowflake Computing Inc.

Initial release

2013

2016

1980

2014

Current release

4.1.0, June 2022

2.0, September 2019

23c, September 2023

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

AGPL v3

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

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Implementation language

C++

Python

Java, Javascript

C and C++

Server operating systems

Linux

hosted

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

hosted

Data scheme

yes

schema-free

yes

Schemaless in JSON and XML columns

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

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

temporal, categorical

yes

SQL

Support of SQL

SQL-like DML and DDL statements

ANSI SQL for query only (using Presto)

yes

with proprietary extensions

yes

APIs and other access methods

JDBC
ODBC

CLI Client
RESTful HTTP API

JDBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

CLI Client
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

Go
Haskell
Java
JavaScript
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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

PL/SQL

also stored procedures in Java possible

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic sharding

Sharding, horizontal partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

isolation level can be parameterized

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes,with MongoDB ord RethinkDB

yes

In-memory capabilities

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

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

Access rights for users can be defined per table

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles and pluggable authentication

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