DBMS > Google Cloud Spanner vs. Hypertable vs. Newts vs. RocksDB vs. SAP IQ

System Properties Comparison Google Cloud Spanner vs. Hypertable vs. Newts vs. RocksDB vs. SAP IQ

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

An open source BigTable implementation based on distributed file systems such as Hadoop

Time Series DBMS based on Cassandra

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

Columnar RDBMS optimized for Big Data analytics

Primary database model

column-oriented

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

Score	2.89
Rank	#103	Overall
	#52	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

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

Score	2.75
Rank	#104	Overall
	#53	Relational DBMS

Website

cloud.google.com/spanner

opennms.github.io/newts

rocksdb.org

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

Technical documentation

cloud.google.com/spanner/docs

github.com/OpenNMS/newts/wiki

github.com/facebook/rocksdb/wiki

help.sap.com/docs/SAP_IQ

Developer

Google

Hypertable Inc.

OpenNMS Group

Facebook, Inc.

SAP, formerly Sybase

Initial release

2017

2009

2014

2013

1994

Current release

0.9.8.11, March 2016

8.11.4, April 2024

16.1 SPS04, April 2019

License

Commercial or Open Source

commercial

Open Source

GNU version 3. Commercial license available

Open Source

Apache 2.0

Open Source

BSD

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

C++

Java

C++

Server operating systems

hosted

Linux
OS X
Windows

an inofficial Windows port is available

Linux
OS X
Windows

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.

Secondary indexes

yes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

yes

Query statements complying to ANSI 2011

yes

APIs and other access methods

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

C++ API
Thrift

HTTP REST
Java API

C++ API
Java API

ADO.NET
JDBC
ODBC
RESTful HTTP API

Supported programming languages

Go
Java
JavaScript (Node.js)
Python

C++
Java
Perl
PHP
Python
Ruby

Java

C
C++
Go
Java
Perl
Python
Ruby

C
C#
C++
Java
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

horizontal partitioning

shared disk or shared nothing architectures with SAP IQ Multiplexer

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication with 3 replicas for regional instances.

selectable replication factor on file system level

selectable replication factor

based on Cassandra

yes

SAP/Sybase Replication Server

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

yes

Transaction concepts

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

ACID

Strict serializable isolation

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 Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

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