DBMS > Apache Impala vs. Blueflood vs. GigaSpaces vs. RocksDB

System Properties Comparison Apache Impala vs. Blueflood vs. GigaSpaces vs. RocksDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Scalable TimeSeries DBMS based on Cassandra

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

Time Series DBMS

Document store
Object oriented DBMS

Values are user defined objects

Key-value store

Secondary database models

Document store

Graph DBMS
Search engine

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	0.13
Rank	#346	Overall
	#33	Time Series DBMS

Score	1.03
Rank	#188	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

Technical documentation

impala.apache.org/impala-docs.html

github.com/rax-maas/blueflood/wiki

docs.gigaspaces.com/latest/landing.html

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Rackspace

Gigaspaces Technologies

Facebook, Inc.

Initial release

2013

2000

2013

Current release

4.1.0, June 2022

15.5, September 2020

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache 2.0

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

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

Implementation language

C++

Java

Java, C++, .Net

C++

Server operating systems

Linux

Linux
OS X

Linux
macOS
Solaris
Windows

Linux

Data scheme

yes

predefined scheme

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

SQL-like DML and DDL statements

SQL-99 for query and DML statements

APIs and other access methods

JDBC
ODBC

HTTP REST

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

C++ API
Java API

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C++
Java
Python
Scala

C
C++
Go
Java
Perl
Python
Ruby

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

based on Cassandra

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

yes

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

based on Cassandra
Immediate Consistency

based on Cassandra

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

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Role-based access control

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.