DBMS > Apache Impala vs. BoltDB vs. GigaSpaces vs. STSdb

System Properties Comparison Apache Impala vs. BoltDB vs. GigaSpaces vs. STSdb

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Relational DBMS

Key-value store

Document store
Object oriented DBMS

Values are user defined objects

Key-value store

Secondary database models

Document store

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Trend Chart

Score	14.03
Rank	#40	Overall
	#24	Relational DBMS

Score	0.76
Rank	#224	Overall
	#32	Key-value stores

Score	1.02
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	0.06
Rank	#365	Overall
	#55	Key-value stores

Website

impala.apache.org

github.com/boltdb/bolt

www.gigaspaces.com

github.com/STSSoft/STSdb4

Technical documentation

impala.apache.org/impala-docs.html

docs.gigaspaces.com/latest/landing.html

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Gigaspaces Technologies

STS Soft SC

Initial release

2013

2000

2011

Current release

4.1.0, June 2022

15.5, September 2020

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

MIT License

Open Source

Apache Version 2; Commercial licenses available

Open Source

GPLv2, commercial license 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

C++

Java, C++, .Net

Server operating systems

Linux

BSD
Linux
OS X
Solaris
Windows

Linux
macOS
Solaris
Windows

Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

SQL-like DML and DDL statements

SQL-99 for query and DML statements

APIs and other access methods

JDBC
ODBC

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

.NET Client API

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C++
Java
Python
Scala

C#
Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Triggers

yes, event driven architecture

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

none

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Foreign keys

Referential integrity

Transaction concepts

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

yes

ACID

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Role-based access control

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More resources

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