DBMS > Altibase vs. Apache Druid vs. GigaSpaces vs. RocksDB

System Properties Comparison Altibase vs. Apache Druid vs. GigaSpaces vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Relational DBMS

Relational DBMS
Time Series DBMS

Document store
Object oriented DBMS

Values are user defined objects

Key-value store

Secondary database models

Graph DBMS
Search engine

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

Score	1.07
Rank	#186	Overall
	#87	Relational DBMS

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	0.97
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

druid.apache.org/docs/latest/design

docs.gigaspaces.com/latest/landing.html

github.com/facebook/rocksdb/wiki

Developer

Altibase

Apache Software Foundation and contributors

Gigaspaces Technologies

Facebook, Inc.

Initial release

1999

2012

2000

2013

Current release

v7.3, 2023, August 2023

29.0.1, April 2024

15.5, September 2020

8.11.4, April 2024

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

Open Source

Apache license v2

Open Source

Apache Version 2; Commercial licenses available

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

Java, C++, .Net

C++

Server operating systems

AIX
HP-UX
Linux

Linux
OS X
Unix

Linux
macOS
Solaris
Windows

Linux

Data scheme

yes

schema-less columns are supported

schema-free

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.

XML can be used for describing objects metadata

Secondary indexes

yes

SQL

Support of SQL

ANSI SQL-92

SQL for querying

SQL-99 for query and DML statements

APIs and other access methods

JDBC
ODBC
Proprietary protocol

JDBC
RESTful HTTP/JSON API

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

C++ API
Java API

Supported programming languages

C
C++
Java

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
C++
Java
Python
Scala

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

stored procedures and stored functions

yes

Triggers

yes

yes, event driven architecture

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, via HDFS, S3 or other storage engines

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Role-based access control

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