DBMS > AlaSQL vs. Apache Impala vs. InfinityDB vs. Oracle vs. PlanetScale

System Properties Comparison AlaSQL vs. Apache Impala vs. InfinityDB vs. Oracle vs. PlanetScale

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Analytic DBMS for Hadoop

A Java embedded Key-Value Store which extends the Java Map interface

Widely used RDBMS

Scalable, distributed, serverless MySQL database platform built on top of Vitess

Primary database model

Document store
Relational DBMS

Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Document store

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

Document store
Spatial DBMS

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

Score	0.46
Rank	#260	Overall
	#40	Document stores
	#121	Relational DBMS

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	0.00
Rank	#378	Overall
	#57	Key-value stores

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	1.59
Rank	#151	Overall
	#70	Relational DBMS

Website

alasql.org

impala.apache.org

boilerbay.com

www.oracle.com/database

planetscale.com

Technical documentation

github.com/AlaSQL/alasql

impala.apache.org/impala-docs.html

boilerbay.com/infinitydb/manual

docs.oracle.com/en/database

planetscale.com/docs

Developer

Andrey Gershun & Mathias R. Wulff

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Boiler Bay Inc.

Oracle

PlanetScale

Initial release

2014

2013

2002

1980

2020

Current release

4.1.0, June 2022

4.0

23c, September 2023

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache Version 2

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

JavaScript

C++

Java

C and C++

Server operating systems

server-less, requires a JavaScript environment (browser, Node.js)

Linux

All OS with a Java VM

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

Docker
Linux
macOS

Data scheme

schema-free

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

yes

Schemaless in JSON and XML columns

yes

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

manual creation possible, using inversions based on multi-value capability

yes

SQL

Support of SQL

Close to SQL99, but no user access control, stored procedures and host language bindings.

SQL-like DML and DDL statements

yes

with proprietary extensions

yes

with proprietary extensions

APIs and other access methods

JavaScript API

JDBC
ODBC

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

JavaScript

All languages supporting JDBC/ODBC

Java

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

PL/SQL

also stored procedures in Java possible

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

none

Multi-source replication
Source-replica replication

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

none

Eventual Consistency

Immediate Consistency

READ-COMMITTED or SERIALIZED

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

manual creation possible, using inversions based on multi-value capability

yes

not for MyISAM storage engine

Transaction concepts

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

yes

only for local storage and DOM-storage

ACID

Optimistic locking for transactions; no isolation for bulk loads

ACID

isolation level can be parameterized

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

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'

yes

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

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