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DBMS > BigchainDB vs. Ingres vs. Microsoft Azure Synapse Analytics vs. Tarantool

System Properties Comparison BigchainDB vs. Ingres vs. Microsoft Azure Synapse Analytics vs. Tarantool

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Editorial information provided by DB-Engines
NameBigchainDB  Xexclude from comparisonIngres  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsWell established RDBMSElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelDocument storeRelational DBMSRelational DBMSDocument store
Key-value store
Relational DBMS
Secondary database modelsSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.79
Rank#212  Overall
#36  Document stores
Score4.11
Rank#81  Overall
#44  Relational DBMS
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Websitewww.bigchaindb.comwww.actian.com/­databases/­ingresazure.microsoft.com/­services/­synapse-analyticswww.tarantool.io
Technical documentationbigchaindb.readthedocs.io/­en/­latestdocs.actian.com/­ingresdocs.microsoft.com/­azure/­synapse-analyticswww.tarantool.io/­en/­doc
DeveloperActian CorporationMicrosoftVK
Initial release20161974 infooriginally developed at University Berkely in early 1970s20162008
Current release11.2, May 20222.10.0, May 2022
License infoCommercial or Open SourceOpen Source infoAGPL v3commercialcommercialOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languagePythonCC++C and C++
Server operating systemsLinuxAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
hostedBSD
Linux
macOS
Data schemeschema-freeyesyesFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or datenoyesyesstring, double, decimal, uuid, integer, blob, boolean, datetime
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nono infobut tools for importing/exporting data from/to XML-files availablenono
Secondary indexesyesyesyes
SQL infoSupport of SQLnoyesyesFull-featured ANSI SQL support
APIs and other access methodsCLI Client
RESTful HTTP API
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
ADO.NET
JDBC
ODBC
Open binary protocol
Supported programming languagesGo
Haskell
Java
JavaScript
Python
Ruby
C#
Java
PHP
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresyesTransact SQLLua, C and SQL stored procedures
Triggersyesnoyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslySharding, horizontal partitioningSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorIngres ReplicatoryesAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyCasual consistency across sharding partitions
Eventual consistency within replicaset partition infowhen using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition infowhen using Raft
Foreign keys infoReferential integritynoyesno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayesyes infoMVCCyesyes, cooperative multitasking
Durability infoSupport for making data persistentyes,with MongoDB ord RethinkDByesyesyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlyesfine grained access rights according to SQL-standardyesAccess 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
BigchainDBIngresMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseTarantool
DB-Engines blog posts

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

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