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DBMS > Hazelcast vs. Microsoft Azure Synapse Analytics vs. Pinecone vs. Tarantool

System Properties Comparison Hazelcast vs. Microsoft Azure Synapse Analytics vs. Pinecone vs. Tarantool

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Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonPinecone  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionA widely adopted in-memory data gridElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerA managed, cloud-native vector databaseIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelKey-value storeRelational DBMSVector DBMSDocument store
Key-value store
Relational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12Spatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.46
Rank#61  Overall
#7  Key-value stores
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score3.23
Rank#92  Overall
#3  Vector DBMS
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Websitehazelcast.comazure.microsoft.com/­services/­synapse-analyticswww.pinecone.iowww.tarantool.io
Technical documentationhazelcast.org/­imdg/­docsdocs.microsoft.com/­azure/­synapse-analyticsdocs.pinecone.io/­docs/­overviewwww.tarantool.io/­en/­doc
DeveloperHazelcastMicrosoftPinecone Systems, IncVK
Initial release2008201620192008
Current release5.3.6, November 20232.10.0, May 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availablecommercialcommercialOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++C and C++
Server operating systemsAll OS with a Java VMhostedhostedBSD
Linux
macOS
Data schemeschema-freeyesFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateyesyesString, Number, Booleanstring, 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.yes infothe object must implement a serialization strategynonono
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL-like query languageyesnoFull-featured ANSI SQL support
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
ADO.NET
JDBC
ODBC
RESTful HTTP APIOpen binary protocol
Supported programming languages.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C#
Java
PHP
PythonC
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresyes infoEvent Listeners, Executor ServicesTransact SQLLua, C and SQL stored procedures
Triggersyes infoEventsnoyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesShardingSharding, 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 nodesyes infoReplicated MapyesAsynchronous 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 methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate 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 integritynono 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 dataone or two-phase-commit; repeatable reads; read commitedACIDACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, cooperative multitasking
Durability infoSupport for making data persistentyesyesyesyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlRole-based access controlyesAccess 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
HazelcastMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehousePineconeTarantool
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