DBMS > GeoSpock vs. Heroic vs. RocksDB vs. SwayDB vs. Tibero

System Properties Comparison GeoSpock vs. Heroic vs. RocksDB vs. SwayDB vs. Tibero

Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

Spatial and temporal data processing engine for extreme data scale

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

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

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

A secure RDBMS, designed for easy portability from Oracle

Primary database model

Secondary database models

Time Series DBMS

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

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

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

Score	0.04
Rank	#387	Overall
	#61	Key-value stores

Score	1.59
Rank	#148	Overall
	#68	Relational DBMS

Website

geospock.com

github.com/spotify/heroic

rocksdb.org

swaydb.simer.au

us.tmaxsoft.com/products/tibero

Technical documentation

spotify.github.io/heroic

github.com/facebook/rocksdb/wiki

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

Developer

GeoSpock

Spotify

Facebook, Inc.

Simer Plaha

TmaxSoft

Initial release

2014

2013

2018

2003

Current release

2.0, September 2019

9.2.1, May 2024

6, April 2015

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

BSD

Open Source

GNU Affero GPL V3.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java, Javascript

Java

C++

Scala

C and Assembler

Server operating systems

hosted

Linux

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

schema-free

yes

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.

yes

Secondary indexes

temporal, categorical

yes

via Elasticsearch

yes

SQL

Support of SQL

ANSI SQL for query only (using Presto)

yes

APIs and other access methods

JDBC

HQL (Heroic Query Language, a JSON-based language)
HTTP API

C++ API
Java API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

Supported programming languages

C
C++
Go
Java
Perl
Python
Ruby

Java
Kotlin
Scala

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

Persistent Stored Procedure (PSM)

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

horizontal partitioning

none

horizontal partitioning

by range, hash, list or composite

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

Atomic execution of operations

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

planned for next version

User concepts

Access control

Access rights for users can be defined per table

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

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