DBMS > AlaSQL vs. Apache Phoenix vs. InfinityDB vs. Oracle vs. TigerGraph

System Properties Comparison AlaSQL vs. Apache Phoenix vs. InfinityDB vs. Oracle vs. TigerGraph

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

A scale-out RDBMS with evolutionary schema built on Apache HBase

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

Widely used RDBMS

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

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

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

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

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	1.83
Rank	#139	Overall
	#13	Graph DBMS

Website

alasql.org

phoenix.apache.org

boilerbay.com

www.oracle.com/database

www.tigergraph.com

Technical documentation

github.com/AlaSQL/alasql

phoenix.apache.org

boilerbay.com/infinitydb/manual

docs.oracle.com/en/database

docs.tigergraph.com

Developer

Andrey Gershun & Mathias R. Wulff

Apache Software Foundation

Boiler Bay Inc.

Oracle

Initial release

2014

2002

1980

2017

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

4.0

23c, September 2023

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache Version 2.0

commercial

restricted free version is available

commercial

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

C and C++

C++

Server operating systems

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

Linux
Unix
Windows

All OS with a Java VM

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

Linux

Data scheme

schema-free

yes

late-bound, schema-on-read capabilities

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.

yes

with proprietary extensions

SQL-like query language (GSQL)

APIs and other access methods

JavaScript API

JDBC

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)

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

JavaScript

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

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

C++
Java

Server-side scripts

Stored procedures

user defined functions

PL/SQL

also stored procedures in Java possible

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

can be realized in PL/SQL

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency or Eventual Consistency

Immediate Consistency

READ-COMMITTED or SERIALIZED

Immediate Consistency

Foreign keys

Referential integrity

yes

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

yes

Relationships in graphs

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

Concurrency

Support for concurrent manipulation of data

yes

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'

User concepts

Access control

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

fine grained access rights according to SQL-standard

Role-based access control

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