DBMS > Riak TS vs. SAP Adaptive Server vs. SQream DB vs. Tarantool

System Properties Comparison Riak TS vs. SAP Adaptive Server vs. SQream DB vs. Tarantool

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Editorial information provided by DB-Engines

Name

Description

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

The SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMS

a GPU-based, columnar RDBMS for big data analytics workloads

In-memory computing platform with a flexible data schema for efficiently building high-performance applications

Primary database model

Time Series DBMS

Relational DBMS

Document store
Key-value store
Relational DBMS

Secondary database models

Spatial DBMS

with Boeing's Spatial Query Server

Spatial DBMS

with Tarantool/GIS extension

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

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Score	35.09
Rank	#25	Overall
	#17	Relational DBMS

Score	0.74
Rank	#224	Overall
	#103	Relational DBMS

Score	1.67
Rank	#143	Overall
	#25	Document stores
	#25	Key-value stores
	#65	Relational DBMS

Website

www.sap.com/products/technology-platform/sybase-ase.html

sqream.com

www.tarantool.io

Technical documentation

www.tiot.jp/riak-docs/riak/ts/latest

help.sap.com/docs/SAP_ASE

docs.sqream.com

www.tarantool.io/en/doc

Developer

Open Source, formerly Basho Technologies

SAP, Sybase

SQream Technologies

Initial release

2015

1987

2017

2008

Current release

3.0.0, September 2022

16.0

2022.1.6, December 2022

2.10.0, May 2022

License

Commercial or Open Source

Open Source

commercial

Open Source

BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise

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

Erlang

C and C++

C++, CUDA, Haskell, Java, Scala

C and C++

Server operating systems

Linux
OS X

AIX
HP-UX
Linux
Solaris
Unix
Windows

Linux

BSD
Linux
macOS

Data scheme

schema-free

yes

Flexible data schema: relational definition for tables with ability to store json-like documents in columns

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

string, double, decimal, uuid, integer, blob, boolean, datetime

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

restricted

yes

SQL

Support of SQL

yes, limited

yes

Full-featured ANSI SQL support

APIs and other access methods

HTTP API
Native Erlang Interface

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

.Net
JDBC
ODBC

Open binary protocol

Supported programming languages

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

C
C++
Cobol
Java
Java
Perl
PHP
Python

C++
Java
JavaScript (Node.js)
Python

C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust

Server-side scripts

Stored procedures

Erlang

Java and Transact-SQL

user defined functions in Python

Lua, C and SQL stored procedures

Triggers

yes

pre-commit hooks and post-commit hooks

yes

yes, before/after data modification events, on replication events, client session events

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

horizontal and vertical partitioning

Sharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication
Source-replica replication

none

Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Casual consistency across sharding partitions
Eventual consistency within replicaset partition

when using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition

when using Raft

Foreign keys

Referential integrity

links between datasets can be stored

yes

Transaction concepts

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

ACID

ACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions

Concurrency

Support for concurrent manipulation of data

yes

yes, cooperative multitasking

Durability

Support for making data persistent

yes

yes, write ahead logging

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes, full featured in-memory storage engine with persistence

User concepts

Access control

fine grained access rights according to SQL-standard

Access Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

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More resources

DB-Engines blog posts

Data processing speed and reliability: in-memory synchronous replication
9 November 2021, Vladimir Perepelytsya, Tarantool (sponsor)

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