DBMS > AlaSQL vs. Apache IoTDB vs. HarperDB vs. Oracle vs. Splunk

System Properties Comparison AlaSQL vs. Apache IoTDB vs. HarperDB vs. Oracle vs. Splunk

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

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.

Widely used RDBMS

Analytics Platform for Big Data

Primary database model

Document store
Relational DBMS

Secondary database models

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	0.51
Rank	#256	Overall
	#40	Document stores
	#118	Relational DBMS

Score	1.31
Rank	#164	Overall
	#14	Time Series DBMS

Score	0.60
Rank	#244	Overall
	#38	Document stores

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Score	89.10
Rank	#14	Overall
	#2	Search engines

Website

alasql.org

iotdb.apache.org

www.harperdb.io

www.oracle.com/database

www.splunk.com

Technical documentation

github.com/AlaSQL/alasql

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

docs.harperdb.io/docs

docs.oracle.com/en/database

docs.splunk.com/Documentation/Splunk

Developer

Andrey Gershun & Mathias R. Wulff

Apache Software Foundation

HarperDB

Oracle

Splunk Inc.

Initial release

2014

2018

2017

1980

2003

Current release

1.1.0, April 2023

3.1, August 2021

23c, September 2023

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache Version 2.0

commercial

free community edition available

commercial

restricted free version is available

commercial

Limited free edition and free developer edition 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

JavaScript

Java

Node.js

C and C++

Server operating systems

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

All OS with a Java VM (>= 1.8)

Linux
OS X

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

Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

dynamic schema

yes

Schemaless in JSON and XML columns

yes

Typing

predefined data types such as float or date

yes

JSON data types

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

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

SQL-like query language

SQL-like data manipulation statements

yes

with proprietary extensions

Splunk Search Processing Language for search commands

APIs and other access methods

JavaScript API

JDBC
Native API

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

HTTP REST

Supported programming languages

JavaScript

C
C#
C++
Go
Java
Python
Scala

.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

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

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Custom Functions

since release 3.1

PL/SQL

also stored procedures in Java possible

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

A table resides as a whole on one (or more) nodes in a cluster

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

yes

the nodes on which a table resides can be defined

Multi-source replication
Source-replica replication

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

can be realized in PL/SQL

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

Atomic execution of specific operations

ACID

isolation level can be parameterized

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

yes, using LMDB

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

yes

Access rights for users and roles

fine grained access rights according to SQL-standard

Access rights for users and roles

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